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June 3, 20260 citationsOpen Access

The Competitive Deployment Dilemma: Market Incentives, Collective Action, and the Policy Conditions for Accountable AI Authority

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AHAlexander Huseby

Key Points

  • This research questions why the governance gap in AI persists and identifies conditions to close it.
  • Examines structural conditions affecting AI governance investment and accountability frameworks.
  • Analyzes regulatory mechanisms, market pricing of governance quality, and polycentric coordination.
  • Reviews case examples including the EU AI Act and AI liability insurance markets.
  • Identifies that organizations fail to invest in AI governance due to private costs and shared benefits.
  • Suggests that governance investment can achieve competitive advantage if structural conditions are met.
  • Concludes that without regulatory and market changes, underinvestment in AI accountability will persist.

Abstract

The three preceding papers in this series established that AI decision-making authority is expanding faster than accountability frameworks can keep pace, applied this finding to documented enterprise deployments, and specified the technical architecture required to maintain meaningful human oversight at each level of the AI Authority Maturity Model (AAMM). This paper addresses the structural question that underlies the governance gap: why does it persist, and under what conditions will it close? The argument is that the governance gap is not primarily a failure of organizational ethics or awareness. It is a collective action problem in the precise sense articulated by Olson (1965): individual organizations rationally underinvest in AI governance because the costs are private and immediate, while the benefits — avoided systemic risk, maintained institutional trust, public confidence in AI systems — are shared and diffuse. No individual organization has sufficient incentive to bear the full cost of accountability architecture when competitors can deploy without it and free-ride on the resulting institutional trust. This structural diagnosis implies that governance investment will remain systematically below socially optimal levels unless structural conditions change. This paper examines three mechanisms that can change those conditions: mandatory minimum standards enforced through regulation, market mechanisms that price governance quality differentially, and polycentric coordination that creates shared governance infrastructure. Drawing on the EU AI Act’s phased enforcement timeline, the emergence of AI liability insurance and ISO/IEC 42001 certification markets, and the limitations of voluntary commitments demonstrated by the Seoul Frontier AI Safety Commitments (2024), the paper concludes by specifying the conditions under which governance investment becomes self-sustaining as a source of competitive advantage rather than a competitive burden. Keywords: collective action, AI governance, competitive dynamics, EU AI Act, AI liability insurance, ISO 42001, voluntary commitments, regulatory policy, polycentric governance, governance premium, AAMM, free-rider problem

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Cite This Study

Alexander Huseby (2026) studied this question.

synapsesocial.com/papers/6a1fc756dee9eb8c0dce829fhttps://doi.org/10.5281/zenodo.20487712
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