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Practical Governance for Enterprise AI

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AI Vendor Governance

Most organizations deploy AI through third parties: foundation model APIs, packaged AI products, and AI-enabled SaaS platforms. This creates a governance problem. The organization is responsible to regulators and customers for AI behavior, but the model, training data, and safety controls belong to the vendor.

The EU AI Act creates specific obligations for organizations deploying AI built on third-party models, including due diligence requirements and contractual provisions. Financial regulators have updated third-party risk management guidance to cover AI vendors. Procurement teams are beginning to require AI transparency reports and audit rights as standard contract terms.

This hub tracks the regulatory requirements, contractual frameworks, and practitioner guidance for governing AI vendors and third-party AI systems.

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ResearchUS2026-05-03

Anthropic's Safety Board Structure Among Frontier AI Governance Mechanisms Analyzed in Harvard Law Review

A March 2026 Harvard Law Review article examines how frontier AI companies such as OpenAI and Anthropic have adopted governance structures designed to counterbalance commercial profit pressures with safety-oriented accountability. The analysis focuses in particular on Anthropic's charter mechanism, which grants Class T shareholders the right to elect three of five board directors either after May 24, 2027 or eight months following the receipt of $6 billion in investment capital, whichever occurs first. These trustees are empowered to prioritize safety considerations, structurally limiting the influence of purely profit-driven incentives at the board level. The research classifies these arrangements as prosocial corporate governance tools and situates them within broader stakeholder-focused approaches to managing AI development risks. For enterprise compliance teams, the analysis provides a framework for evaluating whether AI vendors' internal governance structures credibly constrain high-risk development practices, which is increasingly relevant to third-party risk assessments and AI procurement due diligence. While the article is not a binding instrument, its articulation of concrete governance benchmarks offers practical reference points for assessing AI suppliers against emerging standards.