Updated: February 2026
Regulatory Markets
The creation of a new sector of licensed private regulators who compete to sell regulatory services to AI companies, with governments setting the required outcomes while market forces drive innovation in regulatory technologies capable of keeping pace with AI development.
What it is:
Regulatory markets address two fundamental deficits in AI governance: the technical deficit (governments lack expertise to regulate AI effectively) and the democratic deficit (industry self-regulation lacks public accountability). Under this model, governments define required outcomes — such as labor transition timelines, retraining obligations, or displacement impact thresholds — while licensed private regulators compete to develop and sell compliance services to AI companies.
Regulatory markets could operationalize obligations that are easy to state but hard to enforce: ensuring automation benefits are shared with affected workers, requiring meaningful human oversight of consequential decisions, or mandating that efficiency gains translate into reduced hours rather than reduced headcount.
Recommended Reading:
Gillian Hadfield & Jack Clark
April 2023
Hadfield and Clark argue that existing approaches—including the EU AI Act's risk management requirements and U.S./UK reliance on voluntary standards—"more or less kick the regulatory can down the road" by delegating substantive decisions to private standard-setting bodies without democratic oversight. Their framework envisions governments regulating perhaps 5-10 private regulators rather than thousands of AI companies directly, with regulators facing license suspension or revocation if they fail to achieve required outcomes.
Philip Moreira Tomei, Rupal Jain, Matija Franklin
AI Governance through Markets
March 2025
The authors argue that market governance mechanisms — insurance, auditing, procurement standards, and due diligence — should be considered alongside traditional regulatory frameworks for AI governance. They propose standardized AI disclosures covering data provenance, energy consumption, compute allocation, intended model behavior, interpretability, open-source practices, and adversarial testing as the foundation for market-based governance. The paper directly engages with Hadfield and Clark's regulatory markets proposal, positioning it as "one possible structure within which market governance mechanisms can operate."
Real-world precedents:
Credit rating agencies functioned as private regulatory intermediaries in financial markets but failed catastrophically in 2008 due to inadequate government oversight and deliberate shielding from liability.
Similarly, the FAA's delegation of safety certification to Boeing, which contributed to the 737 MAX crashes, demonstrates the dangers of under-resourced oversight of private regulatory functions.
More successful precedents include the global network of product safety certification bodies (such as UL and TÜV) that test products against government-mandated standards, and professional licensing regimes where private bar associations and medical boards enforce competence standards set by legislatures.
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