AI Governance through Markets
Philip Moreira Tomei, Rupal Jain, Matija Franklin
Abstract
This paper argues that market governance mechanisms should be considered a key approach in the governance of artificial intelligence (AI), alongside traditional regulatory frameworks. While current governance approaches have predominantly focused on regulation, we contend that market-based mechanisms offer effective incentives for responsible AI development. We examine four emerging vectors of market governance: insurance, auditing, procurement, and due diligence, demonstrating how these mechanisms can affirm the relationship between AI risk and financial risk while addressing capital allocation inefficiencies. While we do not claim that market forces alone can adequately protect societal interests, we maintain that standardised AI disclosures and market mechanisms can create powerful incentives for safe and responsible AI development. This paper urges regulators, economists, and machine learning researchers to investigate and implement market-based approaches to AI governance.
Overview
The field of Artificial Intelligence (AI) governance has predominantly emphasised regulatory frameworks and international cooperation to address AI risk. Meanwhile, uncertainty around AI risks is a major barrier to widespread enterprise adoption. Despite economic benefits, organizations recognize AI risk as a business risk and lack the tools to confidently address it. Market governance approaches, such as insurance, auditing, procurement, and due diligence, can serve to both mitigate AI risk and enable AI growth - aligning market forces with prosocial behaviour. Market governance mechanisms are processes that structure economic behaviour by aligning financial incentives with desired outcomes. By directing capital flows, they possess the distinct advantage of embedding their own enforcement and incentive structures. Regulatory initiatives for AI, on the other hand, have faced increasing criticism for being perceived as anticompetitive and anti-growth. We contend that rational and responsible approaches to AI governance can align with economic objectives. Policy interventions may prove instrumental in creating a robust market governance ecosystem. The analysis of the market governance of AI opens up distinct opportunities for both public and private involvement. Mechanisms such as insurance, auditing, due diligence, and procurement offer opportunities for both startups and large enterprises to capitalise on the growing need for AI de-risking which is projected to reach a value of $276 billion by 2030. These mechanisms also afford policymakers and quasi-regulatory entities—including industry consortia, trade associations, and standards organisations — strategic pathways for market shaping. Through the deployment of incentive structures, subsidisation programs, public-private collaborations, and standardisation frameworks, policymakers can leverage markets to govern artificial intelligence development while advancing critical economic, technological, and societal imperatives.
