Corporate Governance for AI-Enabled Decision Systems

Authors

  • Mark Collins Author

Keywords:

corporate governance, artificial intelligence, boards, model risk, accountability

Abstract

This governance perspective examines corporate governance for AI-enabled decision systems. The organizing question is how boards and executives can oversee material algorithmic decisions without reducing oversight to generic principles. Ten related scholarly sources are synthesized through a decision-centered framework spanning problem definition, mechanism, measurement, evaluation, implementation, and governance. The review does not invent experiments, pooled estimates, or unreported quantitative results. It instead evaluates the strength and transferability of the available evidence, with particular attention to assuming technical validation alone satisfies fiduciary and stakeholder obligations. The resulting framework links technical or empirical performance to explicit use conditions and identifies tests that should precede wider adoption in firms using AI in finance, employment, marketing, and operations.

References

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Published

2026-08-05

Issue

Vol. 1 (2026): Archive

Section

Governance Perspective

License

Copyright (c) 2026 Markets, Organizations & Public Value

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This work is licensed under a Creative Commons Attribution 4.0 International License.