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In this episode of AI Today, host Kathleen Walch speaks with Michael Joyce, Enterprise Service Delivery and AI Transformation Leader at Cisco, about what it really takes to move AI from experimentation to operational impact in enterprise project delivery.
Drawing on his experience leading technical program management teams across multiple customers, Michael shares how Cisco is applying generative AI to accelerate service delivery, improve decision quality, and empower project managers. He also founded Cisco’s internal AI Innovator Hub for PMs and helped create an AI for PM playbook, giving teams a repeatable way to apply AI under delivery pressure.
Michael explains why AI projects differ fundamentally from traditional software initiatives, and why treating AI like a new team member through proper onboarding, context engineering, and iterative coaching turns it into a powerful "co-pilot" rather than just another tool. He and Kathleen discuss common pitfalls for AI projects like “shiny AI features” that fail to deliver, and how the CPMAI framework helps teams ask the right questions early, using Business Understanding and the AI Go/No-Go checklist to avoid wasted effort.
A standout story from the podcast is how a high-stakes hospital system cutover illustrates how organizing critical knowledge into AI-supported playbooks enabled faster responses, smoother transitions, and stronger stakeholder confidence. They also explore PMI’s M.O.R.E. vision, the importance of relentlessly reassessing AI initiatives as conditions change, and how project managers can balance speed with accountability to deliver trustworthy, responsible AI.
You’ll hear insights on:
Practical, grounded, and enterprise-focused, this episode offers valuable perspectives for project managers, technology leaders, and decision-makers working to turn AI ambition into dependable business results.
By AI & Data Today4.4
149149 ratings
In this episode of AI Today, host Kathleen Walch speaks with Michael Joyce, Enterprise Service Delivery and AI Transformation Leader at Cisco, about what it really takes to move AI from experimentation to operational impact in enterprise project delivery.
Drawing on his experience leading technical program management teams across multiple customers, Michael shares how Cisco is applying generative AI to accelerate service delivery, improve decision quality, and empower project managers. He also founded Cisco’s internal AI Innovator Hub for PMs and helped create an AI for PM playbook, giving teams a repeatable way to apply AI under delivery pressure.
Michael explains why AI projects differ fundamentally from traditional software initiatives, and why treating AI like a new team member through proper onboarding, context engineering, and iterative coaching turns it into a powerful "co-pilot" rather than just another tool. He and Kathleen discuss common pitfalls for AI projects like “shiny AI features” that fail to deliver, and how the CPMAI framework helps teams ask the right questions early, using Business Understanding and the AI Go/No-Go checklist to avoid wasted effort.
A standout story from the podcast is how a high-stakes hospital system cutover illustrates how organizing critical knowledge into AI-supported playbooks enabled faster responses, smoother transitions, and stronger stakeholder confidence. They also explore PMI’s M.O.R.E. vision, the importance of relentlessly reassessing AI initiatives as conditions change, and how project managers can balance speed with accountability to deliver trustworthy, responsible AI.
You’ll hear insights on:
Practical, grounded, and enterprise-focused, this episode offers valuable perspectives for project managers, technology leaders, and decision-makers working to turn AI ambition into dependable business results.

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