Beyond the Framework: Operationalizing AI Governance Where Failure Matters
Abstract:
Many organizations have adopted responsible AI principles and governance frameworks, but fewer are prepared to apply them when an AI-enabled system creates risk or produces an unexpected outcome. This presentation explores the gap between having an AI governance framework and being operationally ready to use it.
The discussion will focus on practical issues such as decision ownership, accountability, escalation, and connecting AI governance with existing cybersecurity, data, compliance, and system engineering processes. Attendees will leave with practical considerations for moving from broad principles to clearer roles, controls, and implementation readiness.
Date and Time
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- One Camino Santa Maria
- St. Mary's University
- San Antonio, Texas
- United States 78228
- Building: Blank Sheppard Innovation Center (BSIC)
- Room Number: BSIC 203
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- Starts 05 August 2026 05:00 AM UTC
- Ends 06 October 2026 05:00 AM UTC
- No Admission Charge
Speakers
Bio
Jess J. Montgomery is an AI governance and technology leader with more than two decades of experience leading complex programs across government, defense, cloud transformation, and emerging technologies. She currently serves as a Cloud Computing Engineer Lead supporting U.S. Air Force digital transformation initiatives, where her work focuses on operationalizing AI capabilities within secure, mission-critical environments.
Her work centers on bridging the gap between AI governance frameworks and practical implementation. Her areas of focus include responsible AI, organizational readiness, AI-enabled decision-making, enterprise adoption, and the integration of emerging technologies within regulated and high-consequence environments.
Jess is currently pursuing a Doctor of Computer Science in Big Data Analytics and Artificial Intelligence, where her research examines organizational readiness for AI governance. She is also a CIO.com contributor and speaks on AI governance, enterprise AI strategy, and the practical challenges of implementing accountable and trusted AI.
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