AI Today
AI as Your New Team Member: Scaling with Confidence – with Michael Joyce
Why It Matters
As AI becomes a core capability across enterprises, understanding how to integrate it responsibly and effectively is critical for project success and ROI. This episode offers actionable guidance for PMs and leaders to avoid common pitfalls—such as over‑promising and under‑delivering—by focusing on data readiness, governance, and a co‑pilot mindset, making the insights immediately relevant for teams looking to scale AI with confidence.
Key Takeaways
- •CPM AI certification creates common AI project language.
- •Treat AI as a new team member, onboard with context.
- •AI shifts PM role to decision‑making, not admin tasks.
- •Data quality and context prevent AI feature disappointment.
- •Iterative, business‑first approach drives trusted AI adoption.
Pulse Analysis
In this 31‑minute episode of AI Today, PMI host Kathleen Walsh interviews Michael Joyce, Cisco’s enterprise service‑delivery leader, about embedding generative AI into large‑scale projects. Joyce explains how the newly launched PMI CPM AI certification gave his team a shared vocabulary and repeatable playbook, turning vague AI hype into concrete delivery standards. By aligning technical and business perspectives, the framework helps Cisco accelerate decision‑making, reduce miscommunication, and demonstrate measurable outcomes that executives demand. The discussion also touches on scaling AI across Cisco’s East Coast enterprise portfolio.
Joyce treats AI like a new hire, emphasizing polite prompts, context engineering, and continuous feedback loops. This mindset transforms routine tasks—meeting minutes, SOW summarizations, and risk assessments—into interactive co‑pilot experiences that surface assumptions, flag anomalies, and draft next‑step communications. Project managers move up the value chain, spending less time on admin work and more time aligning stakeholders, refining scope, and driving faster execution. The episode highlights real‑time note‑taking as a low‑risk entry point that instantly frees PMs to focus on strategic decision‑making. These capabilities scale across global delivery teams, amplifying consistency.
The conversation also warns against shipping shiny AI buttons without solid data and context, likening premature releases to Microsoft’s Clippy. CPM AI’s first phase forces teams to ask nine business‑fit questions, ensuring that models are production‑ready and users will actually adopt them. Joyce shares a hospital telephony cut‑over where AI‑generated runbooks turned a high‑risk upgrade into a trusted help‑desk experience, delivering faster resolution and measurable cost savings. By reframing AI from a feature to a decision‑support tool, PMs can manage stakeholder perception, maintain ROI confidence, and continuously reassess outcomes. Such disciplined rollout builds long‑term trust and competitive advantage.
Episode Description
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:
How PMI-CPMAI establishes a common language between business and technical teams
Why chasing “shiny” AI features without understanding why often fails
How treating AI like a teammate leads to stronger results
How project leaders can balance speed with accountability in responsible AI
How project managers are evolving into orchestrators of AI-enabled workflows
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.
Comments
Want to join the conversation?
Loading comments...