When AI Gets It Wrong and Nobody Notices: Governance, Accountability, and the Cost

Description

Most AI governance discourse focuses on model-level risks: bias in training data, lack of explainability, regulatory non-compliance. These are real problems. However, the governance failures that cause the most damage in practice are not model failures—they are organizational failures. They happen when no human in the process has clear accountability for verifying AI outputs, when the speed of AI-assisted analysis creates institutional pressure to skip the validation step, and when the systems that should catch errors are themselves partially automated. 

In high-stakes environments—government, healthcare systems, public infrastructure, financial services—these organizational governance gaps are not hypothetical. They are operational realities with measurable human costs.

This is not a theoretical presentation about responsible AI. It is a direct account of what governance looks like when the stakes are real, the scrutiny is constant, and the humans in the loop must be able to explain every decision to a federal auditor.

Key Takeaways:

• The three organizational conditions that allow AI errors to compound undetected in high-stakes environments, and the governance structures that interrupt each one.
• How to design human-in-the-loop validation checkpoints that are genuinely effective rather than performative, including the accountability assignment that makes them function under operational pressure.
• A practical AI governance framework drawn from federal program management practice that is transferable to any high-stakes delivery environment.
• How to build the documentation and traceability practices that make AI-assisted decisions auditable, defensible, and correctable after the fact.
• Why the accountability gap between AI output and human responsibility is the most consequential and least addressed dimension of AI governance in organizations today, and what closing it actually requires.

Includes 1 HRCI CEU/SHRM PDC

About the Presenter

Dr. Tricia Diamond is a portfolio and program management executive, aerospace engineer, and organizational strategist with more than two decades of leadership across the public sector, technology, and consulting in the United States and the Netherlands. She holds a PhD in Aerospace Engineering and professional aviation experience, alongside advanced credentials including the PMP®, PMI-ACP®, PMO-CP®, CPMAI, GPM-b®, CAL®, ITIL®, AWS-CCP, AWS-AIP, MCASE. As Director of ARPA Implementation for a major U.S. city, she built and led a PMO governing a $386M federal recovery portfolio with 100% regulatory compliance. She has spoken at ASPA and PMI conferences, previously served as VP of Professional Development for PMI Puget Sound, and is a Seattle Parks and Recreation Commissioner. She is the founder of Diamond PMO Solutions, an MWBE owned management consultancy specializing in portfolio governance, PMO design, and organizational strategy as well as PMI certification trainings.