Board Oversight of Generative Artificial Intelligence Use

Roberto Santoro

Board Oversight of Generative Artificial Intelligence Use

Author(s)	Dr. Roberto Santoro
Country	United States
Abstract	Generative Artificial Intelligence is expanding from experimental technology into organizational applications involving analysis, communication, software development, knowledge retrieval, forecasting support, document preparation, and decision assistance. Its accessibility creates an unusual governance challenge because adoption can occur rapidly through both centrally approved systems and decentralized employee use. Boards of directors are therefore required to understand not only the strategic opportunities associated with generative models but also whether management has established suitable boundaries for data protection, model reliability, intellectual-property exposure, cybersecurity, human accountability, third-party dependence, and escalation of material incidents. This study develops a board-level governance framework for overseeing organizational use of Generative Artificial Intelligence without transferring operational model management to directors. Because authenticated corporate board data were not supplied, the quantitative component is explicitly structured as a simulation-based methodological study. Seventy-two synthetic board-governance profiles are evaluated across six generative-AI use scenarios, producing 432 simulated board-risk assessments. A Board Generative AI Oversight Maturity Index is developed from six dimensions: strategic authorization, use-case visibility, data and intellectual-property governance, model-risk control, human accountability, and monitoring and escalation readiness. A complementary Generative AI Risk Recognition Score evaluates whether boards identify and prioritize material risks arising from proposed organizational use. Simulated analysis indicates that recognition performance increases from 48 points under ad hoc adoption to 90 points under assured and adaptive oversight. The study argues that effective board oversight should neither consist of passive reliance on management nor involve directors approving individual prompts and model configurations. Instead, boards should establish risk appetite, require transparent inventories of material applications, clarify accountable ownership, demand reliable assurance information, and ensure that significant incidents can be escalated. The framework provides a testable basis for future empirical research on board governance of generative technologies.
Keywords	Generative Artificial Intelligence, board oversight, corporate governance, AI governance, model risk, digital risk, responsible AI, board accountability
Field	Engineering
Published In	Volume 6, Issue 4, July-August 2025
Published On	2025-08-31

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American Journal of Advanced Multidisciplinary Innovation and Research

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Board Oversight of Generative Artificial Intelligence Use

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