AI Today
How PMOs Lead Responsible AI Transformation in Higher Education – with Ivonne Mejia
AI Today
•March 4, 2026•25 min
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AI Today•Mar 4, 2026
Why It Matters
As universities grapple with limited resources and heightened ethical concerns around student data, a disciplined, PMO‑led approach ensures AI initiatives deliver real value and avoid costly missteps. This episode offers actionable guidance for project professionals seeking to lead AI adoption responsibly and strategically in complex, multi‑campus environments.
Key Takeaways
- •Define business problem before selecting AI solution.
- •Assess data, risk, and readiness during intake.
- •PMOs must embed trustworthy AI throughout project lifecycle.
- •Iterative CPM AI phases enable continuous reassessment.
- •Stakeholder communication shapes perception and project success.
Pulse Analysis
The episode spotlights Ivonne Mejia, lead project portfolio manager for the California State University Bay Region, as she translates PMI’s CPM‑AI framework into a real‑world higher‑education setting. She stresses that AI initiatives must begin with a clear business understanding, not with algorithms, and that data availability, quality, and ethical considerations are evaluated before any model is built. By embedding the six CPM‑AI phases—business understanding, data understanding, preparation, model development, evaluation, and operationalization—her unified PMO creates a disciplined intake process that filters out projects where AI adds no value. This front‑loading reduces wasted effort and aligns AI work with institutional goals.
Mejia argues that university PMOs need three mindset shifts to become AI transformation leaders. First, they must treat AI initiatives as a strategic portfolio rather than isolated projects, prioritizing investments based on value, readiness, and risk. Second, PMOs should become data‑driven, leveraging AI tools for capacity planning, risk forecasting, and predictive analytics. Third, governance must evolve to address bias, privacy, and compliance from day one, using the trustworthy AI principles embedded in CPM‑AI. In practice, this means the PMO acts as a bridge between academic innovators, administrative units, and compliance officers, turning AI governance into a proactive, strategic function.
The conversation also highlights how continuous stakeholder engagement and iterative reassessment drive success. CPM‑AI’s go‑no‑go checkpoints keep teams aligned with changing data policies, federal regulations, and shifting university priorities, allowing rapid pivots without costly rework. By communicating early, measuring KPIs such as reduced processing time or improved student retention, PMOs shape perception and build trust across faculty, staff, and students. Finally, Mejia notes that upskilling through affordable CPM‑AI training lowers failure rates, positioning PMOs to champion responsible AI while delivering measurable outcomes. The episode offers a practical roadmap for higher‑education institutions seeking sustainable, ethical AI transformation.
Episode Description
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.
Show Notes
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