\n

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"};

\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

References-<\/p>\n\n\n\n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

References-<\/p>\n\n\n\n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

References-<\/p>\n\n\n\n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

References-<\/p>\n\n\n\n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

Summary<\/strong><\/p>\n\n\n\n

Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

References-<\/p>\n\n\n\n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n\n\n\n\n

Summary<\/strong><\/p>\n\n\n\n

Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

(The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

References-<\/p>\n\n\n\n

https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

<\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

  • Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

    Summary<\/strong><\/p>\n\n\n\n

    Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

    As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

    (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

    References-<\/p>\n\n\n\n

    https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

    AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

    https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

    Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

    Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

    <\/p>\n\n\n\n

    <\/p>\n\n\n\n

    <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

      \n
    1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

      Summary<\/strong><\/p>\n\n\n\n

      Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

      As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

      (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

      References-<\/p>\n\n\n\n

      https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

      AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

      https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

      Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

      Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

      <\/p>\n\n\n\n

      <\/p>\n\n\n\n

      <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

      Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

        \n
      1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

        Summary<\/strong><\/p>\n\n\n\n

        Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

        As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

        (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

        References-<\/p>\n\n\n\n

        https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

        AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

        https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

        Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

        Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

        <\/p>\n\n\n\n

        <\/p>\n\n\n\n

        <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

      2. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

        Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

          \n
        1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

          Summary<\/strong><\/p>\n\n\n\n

          Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

          As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

          (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

          References-<\/p>\n\n\n\n

          https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

          AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

          https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

          Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

          Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

          <\/p>\n\n\n\n

          <\/p>\n\n\n\n

          <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

        2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
        3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

          Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

            \n
          1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

            Summary<\/strong><\/p>\n\n\n\n

            Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

            As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

            (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

            References-<\/p>\n\n\n\n

            https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

            AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

            https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

            Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

            Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

            <\/p>\n\n\n\n

            <\/p>\n\n\n\n

            <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

          2. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
          3. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
          4. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

            Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

              \n
            1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

              Summary<\/strong><\/p>\n\n\n\n

              Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

              As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

              (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

              References-<\/p>\n\n\n\n

              https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

              AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

              https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

              Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

              Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

              <\/p>\n\n\n\n

              <\/p>\n\n\n\n

              <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                \n
              1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
              2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
              3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                  \n
                1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                  Summary<\/strong><\/p>\n\n\n\n

                  Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                  As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                  (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                  References-<\/p>\n\n\n\n

                  https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                  AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                  https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                  Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                  Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                  <\/p>\n\n\n\n

                  <\/p>\n\n\n\n

                  <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                  Medium Impact Stages<\/strong><\/p>\n\n\n\n

                    \n
                  1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                  2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                  3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                    Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                      \n
                    1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                      Summary<\/strong><\/p>\n\n\n\n

                      Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                      As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                      (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                      References-<\/p>\n\n\n\n

                      https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                      AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                      https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                      Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                      Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                      <\/p>\n\n\n\n

                      <\/p>\n\n\n\n

                      <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                    2. Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n

                      Medium Impact Stages<\/strong><\/p>\n\n\n\n

                        \n
                      1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                      2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                      3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                        Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                          \n
                        1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                          Summary<\/strong><\/p>\n\n\n\n

                          Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                          As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                          (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                          References-<\/p>\n\n\n\n

                          https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                          AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                          https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                          Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                          Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                          <\/p>\n\n\n\n

                          <\/p>\n\n\n\n

                          <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                        2. Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
                        3. Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n

                          Medium Impact Stages<\/strong><\/p>\n\n\n\n

                            \n
                          1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                          2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                          3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                            Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                              \n
                            1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                              Summary<\/strong><\/p>\n\n\n\n

                              Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                              As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                              (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                              References-<\/p>\n\n\n\n

                              https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                              AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                              https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                              Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                              Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                              <\/p>\n\n\n\n

                              <\/p>\n\n\n\n

                              <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                            2. Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
                            3. Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
                            4. Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n

                              Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                \n
                              1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                              2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                              3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                                Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                  \n
                                1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                                  Summary<\/strong><\/p>\n\n\n\n

                                  Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                                  As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                                  (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                                  References-<\/p>\n\n\n\n

                                  https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                                  AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                                  https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                                  Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                  Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                  <\/p>\n\n\n\n

                                  <\/p>\n\n\n\n

                                  <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                                    \n
                                  1. Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
                                  2. Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
                                  3. Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n

                                    Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                      \n
                                    1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                                    2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                                    3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                                      Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                        \n
                                      1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                                        Summary<\/strong><\/p>\n\n\n\n

                                        Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                                        As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                                        (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                                        References-<\/p>\n\n\n\n

                                        https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                                        AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                                        https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                                        Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                        Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                        <\/p>\n\n\n\n

                                        <\/p>\n\n\n\n

                                        <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                                        High Impact Stages<\/strong><\/p>\n\n\n\n

                                          \n
                                        1. Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
                                        2. Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
                                        3. Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n

                                          Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                            \n
                                          1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                                          2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                                          3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                                            Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                              \n
                                            1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                                              Summary<\/strong><\/p>\n\n\n\n

                                              Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                                              As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                                              (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                                              References-<\/p>\n\n\n\n

                                              https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                                              AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                                              https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                                              Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                              Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                              <\/p>\n\n\n\n

                                              <\/p>\n\n\n\n

                                              <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                                              AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n

                                              High Impact Stages<\/strong><\/p>\n\n\n\n

                                                \n
                                              1. Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
                                              2. Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
                                              3. Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n

                                                Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                  \n
                                                1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                                                2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                                                3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                                                  Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                    \n
                                                  1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                                                    Summary<\/strong><\/p>\n\n\n\n

                                                    Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                                                    As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                                                    (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                                                    References-<\/p>\n\n\n\n

                                                    https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                                                    AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                                                    https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                                                    Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                    Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                    <\/p>\n\n\n\n

                                                    <\/p>\n\n\n\n

                                                    <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                                                    AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n

                                                    AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n

                                                    High Impact Stages<\/strong><\/p>\n\n\n\n

                                                      \n
                                                    1. Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
                                                    2. Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
                                                    3. Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n

                                                      Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                        \n
                                                      1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                                                      2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                                                      3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                                                        Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                          \n
                                                        1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                                                          Summary<\/strong><\/p>\n\n\n\n

                                                          Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                                                          As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                                                          (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                                                          References-<\/p>\n\n\n\n

                                                          https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                                                          AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                                                          https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                                                          Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                          Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                          <\/p>\n\n\n\n

                                                          <\/p>\n\n\n\n

                                                          <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n\n\n\n\n

                                                          AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n

                                                          AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n

                                                          High Impact Stages<\/strong><\/p>\n\n\n\n

                                                            \n
                                                          1. Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
                                                          2. Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
                                                          3. Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n

                                                            Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                              \n
                                                            1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                                                            2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                                                            3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                                                              Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                                \n
                                                              1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                                                                Summary<\/strong><\/p>\n\n\n\n

                                                                Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                                                                As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                                                                (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                                                                References-<\/p>\n\n\n\n

                                                                https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                                                                AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                                                                https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                                                                Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                                Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                                <\/p>\n\n\n\n

                                                                <\/p>\n\n\n\n

                                                                <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                                                                Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n

                                                                AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n

                                                                AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n

                                                                High Impact Stages<\/strong><\/p>\n\n\n\n

                                                                  \n
                                                                1. Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
                                                                2. Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
                                                                3. Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n

                                                                  Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                                    \n
                                                                  1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                                                                  2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                                                                  3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                                                                    Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                                      \n
                                                                    1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                                                                      Summary<\/strong><\/p>\n\n\n\n

                                                                      Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                                                                      As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                                                                      (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                                                                      References-<\/p>\n\n\n\n

                                                                      https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                                                                      AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                                                                      https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                                                                      Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                                      Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                                      <\/p>\n\n\n\n

                                                                      <\/p>\n\n\n\n

                                                                      <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                                                                    2. Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n

                                                                      Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n

                                                                      AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n

                                                                      AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n

                                                                      High Impact Stages<\/strong><\/p>\n\n\n\n

                                                                        \n
                                                                      1. Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
                                                                      2. Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
                                                                      3. Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n

                                                                        Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                                          \n
                                                                        1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                                                                        2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                                                                        3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                                                                          Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                                            \n
                                                                          1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                                                                            Summary<\/strong><\/p>\n\n\n\n

                                                                            Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                                                                            As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                                                                            (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                                                                            References-<\/p>\n\n\n\n

                                                                            https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                                                                            AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                                                                            https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                                                                            Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                                            Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                                            <\/p>\n\n\n\n

                                                                            <\/p>\n\n\n\n

                                                                            <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                                                                          2. Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
                                                                          3. Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n

                                                                            Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n

                                                                            AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n

                                                                            AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n

                                                                            High Impact Stages<\/strong><\/p>\n\n\n\n

                                                                              \n
                                                                            1. Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
                                                                            2. Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
                                                                            3. Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n

                                                                              Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                                                \n
                                                                              1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                                                                              2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                                                                              3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                                                                                Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                                                  \n
                                                                                1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                                                                                  Summary<\/strong><\/p>\n\n\n\n

                                                                                  Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                                                                                  As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                                                                                  (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                                                                                  References-<\/p>\n\n\n\n

                                                                                  https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                                                                                  AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                                                                                  https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                                                                                  Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                                                  Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                                                  <\/p>\n\n\n\n

                                                                                  <\/p>\n\n\n\n

                                                                                  <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                                                                                2. Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
                                                                                3. Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
                                                                                4. Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n

                                                                                  Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n

                                                                                  AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n

                                                                                  AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n

                                                                                  High Impact Stages<\/strong><\/p>\n\n\n\n

                                                                                    \n
                                                                                  1. Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
                                                                                  2. Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
                                                                                  3. Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n

                                                                                    Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                                                      \n
                                                                                    1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                                                                                    2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                                                                                    3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                                                                                      Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                                                        \n
                                                                                      1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                                                                                        Summary<\/strong><\/p>\n\n\n\n

                                                                                        Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                                                                                        As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                                                                                        (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                                                                                        References-<\/p>\n\n\n\n

                                                                                        https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                                                                                        AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                                                                                        https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                                                                                        Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                                                        Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                                                        <\/p>\n\n\n\n

                                                                                        <\/p>\n\n\n\n

                                                                                        <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n

                                                                                      2. Big Room Planning:<\/strong> AI simulates different PI planning scenarios, recommending optimal resource allocation and cross-team dependencies.<\/li>\n\n\n\n
                                                                                      3. Program Execution:<\/strong> AI tracks features across teams, providing alerts when timelines deviate and effectively managing dependencies.<\/li>\n\n\n\n
                                                                                      4. Value Stream Management:<\/strong> AI prioritizes portfolio-level requirements dynamically, linking strategy to execution.<\/li>\n\n\n\n
                                                                                      5. Release Management:<\/strong> AI predicts release readiness, highlighting incomplete work or quality issues while automating quality gates.<\/li>\n<\/ul>\n\n\n\n

                                                                                        Much of the time spent on group activities could become superfluous. For example, daily stand-ups may become less frequent, and big-room planning could reduce from days to hours. While individuals and interactions will still be valued, the focus will shift to quality interactions rather than formalized ceremonies. This shift may increase the need for higher emotional intelligence (EQ) among team members to maintain connections and collaboration in the limited time for formal interactions. Smaller teams may face challenges, such as conflicts leading to workflow paralysis. Sprint cycles are set to fall. Advantages between competitors would need to come from a lot more creativity of individual team members than from speed of delivery.<\/p>\n\n\n\n\n\n\n\n

                                                                                        AI and the Agile Software Development Cycle<\/strong><\/p>\n\n\n\n

                                                                                        AI tools already impact various stages of the software development lifecycle. Here is how:<\/p>\n\n\n\n

                                                                                        High Impact Stages<\/strong><\/p>\n\n\n\n

                                                                                          \n
                                                                                        1. Requirements Gathering & Analysis:<\/strong> AI can automate user story generation from stakeholder input, analyse feedback, and predict missing requirements using historical data.<\/li>\n\n\n\n
                                                                                        2. Coding\/Development:<\/strong> Tools like GitHub Copilot provide code suggestions, complete functions, and automate repetitive tasks. AI can also detect vulnerabilities and ensure adherence to coding standards in real-time.<\/li>\n\n\n\n
                                                                                        3. Testing:<\/strong> AI-driven automated testing frameworks generate test cases, identify edge cases, and conduct regression testing, significantly reducing manual effort.<\/li>\n<\/ol>\n\n\n\n

                                                                                          Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                                                            \n
                                                                                          1. Planning & Project Management:<\/strong> AI enhances sprint planning by analysing past performance and predicting risks, though human oversight remains necessary.<\/li>\n\n\n\n
                                                                                          2. Deployment:<\/strong> AI optimizes deployment strategies by predicting failure points and automating rollback processes. Predictive analytics refine release planning.<\/li>\n\n\n\n
                                                                                          3. Design & Architecture:<\/strong> AI generates design templates, recommends architectures, and detects inefficiencies, enabling rapid wire-framing and prototyping.<\/li>\n<\/ol>\n\n\n\n

                                                                                            Low to Medium Impact Stages<\/strong><\/p>\n\n\n\n

                                                                                              \n
                                                                                            1. Maintenance & Support:<\/strong> While AI-driven tools monitor system health and predict issues, complex problems still require hands-on debugging. Chatbots assist with user queries but cannot address large-scale infrastructure fixes.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n

                                                                                              Summary<\/strong><\/p>\n\n\n\n

                                                                                              Agile methods will continue to play a significant role at the team and enterprise levels. However, as productivity, outcomes and speed improve with AI, we may see a shift towards smaller teams, even at the Teams-of-Teams level. The saying, \u201cPeople who know AI will replace those who don\u2019t,\u201d may hold some truth, but the replacement will not likely to be one-to-one. Soft skills, especially emotional intelligence, will become critical in distributed teams using AI tools. Traditional Agile roles like Scrum Master, Product Owner, and Developer will evolve, with overlapping responsibilities requiring greater adaptability and hence could be redefined<\/p>\n\n\n\n

                                                                                              As Agile evolves alongside AI, its foundational principles\u2014collaboration, adaptability, and customer focus\u2014will remain essential. While AI tools promise to enhance efficiency and decision-making, the human element will remain irreplaceable, ensuring Agile frameworks continue to thrive in the face of technological change.<\/p>\n\n\n\n

                                                                                              (The opinion expressed in the article are only that of the Author and not of PM-Powerconsulting<\/em>)<\/p>\n\n\n\n

                                                                                              References-<\/p>\n\n\n\n

                                                                                              https:\/\/mohammedbrueckner.medium.com\/is-ai-killing-agile-bdd4c968388d<\/a><\/p>\n\n\n\n

                                                                                              AI in Agile: What\u2019s Working and What\u2019s Not? | GenAI | Cprime<\/a><\/p>\n\n\n\n

                                                                                              https:\/\/www.project-syndicate.org\/magazine\/ai-is-part-of-larger-technological-revolution-by-carlota-perez-1-2024-03<\/a><\/p>\n\n\n\n

                                                                                              Leadership principles in the Generative AI age \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                                                              Middle Managers &  Leadership Styles (Blogging with AI) \u2013 PM Power Consulting<\/a><\/p>\n\n\n\n

                                                                                              <\/p>\n\n\n\n

                                                                                              <\/p>\n\n\n\n

                                                                                              <\/p>\n","post_title":"NextGen Agile meets NewGen AI","post_excerpt":"With AI tools evolving Agile is likely to even more become \"Agile\" and some of the framework elements will most likely be impacted. The Blog explores this.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"nextgen-agile-meets-nextgen-ai","to_ping":"","pinged":"","post_modified":"2025-02-04 08:34:07","post_modified_gmt":"2025-02-04 03:04:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.pm-powerconsulting.com\/?p=999540","menu_order":0,"post_type":"post","post_mime_type":"","comment_count":"0","filter":"raw"}],"next":false,"prev":false,"total_page":1},"paged":1,"column_class":"jeg_col_3o3","class":"epic_block_11"}; \n