Healthcare Leaders Tackle Three Urgent AI Governance Gaps
Trustible CEO Gerald Kierce led an executive working session at the Coalition for Health AI Leadership Summit, bringing together practitioners from Mass General Brigham, MD Anderson, and a major managed care provider to discuss how governance programs actually work in practice.
The session identified three operational problems that healthcare organizations face as they deploy AI systems.
Keeping Pace With Agentic AI
Agentic AI-systems that can make decisions and take actions with minimal human intervention-moves faster than traditional intake and approval processes. Existing governance frameworks struggle to keep up with the capabilities these systems gain after deployment.
Holding Vendors Accountable
Healthcare organizations sign contracts with vendors, then watch those vendors add AI capabilities months or years later. Current contractual structures don't address how to manage, monitor, or restrict those new features after the agreement is signed.
This matters because vendors control what gets added, but healthcare organizations bear the compliance risk.
Measuring AI Value for Finance Leaders
CFOs need portfolio-level metrics: which AI investments return money, which drain resources, and where risk sits. Most healthcare organizations lack standard ways to report AI ROI in terms finance teams understand.
The healthcare context makes these questions more than academic. Patient safety, regulatory compliance, and liability exposure hinge on how well governance works.
For healthcare professionals implementing or overseeing AI systems, these three areas represent concrete gaps to address now. Learn more about AI for Healthcare and AI for Executives & Strategy to build stronger governance in your organization.
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