In this episode of AI Today, host Kathleen Walch sits down with Sumathi Arcot, Project Director for Lean Agile Transformation in AstraZeneca’s U.S. Oncology Business Unit, for a candid conversation on what it really takes to manage AI responsibly in one of the world’s most regulated industries.

Sumathi shares how the CPMAI methodology fundamentally shifted her perspective on AI, from something experimental and exploratory to a product discipline with defined outcomes, built-in governance, and clear success criteria from day one. In a pharma environment shaped by strict compliance requirements, she explains how CPMAI doesn’t slow innovation—it enables it—by aligning seamlessly with privacy impact assessments, third‑party risk reviews, and regulatory expectations.

Drawing on a real-world patient value impact analysis project in the rare diseases space, Sumathi highlights how CPMAI’s six phases—especially Phase I: Business Understanding and Phase II: Data Understanding—help teams focus on the right problem before model development begins. She also connects CPMAI to PMI’s M.O.R.E. vision, explaining how structured artifacts, KPIs, and go/no-go checkpoints help project managers move beyond delivery to value especially when navigating AI initiatives with diverse, risk-aware stakeholders.

You’ll hear insights on:

• How CPMAI transforms AI experiments into governed, auditable products
• Why Business Understanding is critical in AI initiatives
• How pharma compliance aligns to CPMAI checkpoints
• How the PMI M.O.R.E. vision helps project managers communicate AI value
• What agentic AI and human‑in‑the‑loop leadership looks like in the years ahead

Whether you’re a project manager, transformation leader, or AI practitioner, this episode offers practical lessons for leading AI initiatives where the stakes and the scrutiny are high.

In this episode of AI Today, host Kathleen Walch talks with Ivonne Mejia, Lead Project Portfolio Manager for the San Francisco Bay Region Network at California State University (CSU), to discuss how PMOs can drive responsible AI transformation in higher education.

As multiple CSU campuses consolidate under one unified PMO, Ivonne shares how she's embedding CPMAI into portfolio intake, prioritization, and oversight, ensuring AI initiatives are strategically aligned and governed. She makes the case for how CPMAI Phase One: Business Understanding shifts the question from “How do we build this with AI?” to “Should we?”

The conversation covers readiness assessment, outcome definition, ethics, and stakeholder alignment. Additionally, Ivonne connects her approach to PMI’s M.O.R.E. vision: managing perceptions, owning success, relentlessly reassessing, and expanding perspectives as data and policy evolve.

Tune in to hear about:

• How CPMAI prevents costly missteps
• Why starting with the right business problem changes everything
• How iterative go/no-go decisions keep AI projects aligned and on track
• What the future of AI-augmented project leadership looks like

This episode delivers practical insight into leading AI initiatives that are aligned, governed, and built for measurable impact.

In this episode of AI Today, host Kathleen Walch is joined by Michael Hyzy, Vice President of AI Strategy and Product Development at CGI, to explore why so many AI initiatives struggle—and why methodology matters more than ever.

Drawing on his experience leading enterprise AI initiatives in regulated industries, Michael explains why treating AI like traditional software often leads to failure, stalled pilots, and unmet expectations. He shares how CPMAI provides the structure needed to manage uncertainty, align stakeholders, and move AI efforts from experimentation to measurable business outcomes.

This conversation dives into the realities of managing non-linear AI work, from data readiness and model risk to governance, ethics, and long-term operationalization. Michael also looks ahead to the rise of AI agents and what project leaders must do now to prepare for a future where humans and AI systems work side by side.

Tune in to hear about:

• Why AI projects fail when traditional delivery methods are applied
• How CPMAI helps teams navigate data uncertainty and iterative learning
• How organizations move AI from pilots to production
• Why governance and risk management must be built into AI projects from the start
• What mindset shifts do project managers need when leading AI initiatives
• What the transition from AI tools to AI agents means for organizations

Whether you’re a project manager, AI practitioner, or organizational leader, this episode offers practical insight into delivering AI responsibly, realistically, and at scale.