This article provides a critical policy analysis of Thailand's artificial intelligence (AI) and data governance architecture, examining the National AI Strategy (2022–2027), the Personal Data Protection Act (PDPA), the Draft AI Bill, and the expanding ecosystem of soft-law governance instruments. Applying four complementary theoretical frameworks (Easton's (1965) authoritative allocation of values, Ansell and Gash's (2008) collaborative governance, consequentialist versus deontological ethics, and Bradford's (2020) Brussels Effect theory), the analysis evaluates the effectiveness of Thailand's multi-layered governance approach across ethical, institutional, and strategic dimensions. Drawing on government publications, international reports, and legal analyses, the article identifies four critical structural gaps: a legislative vacuum in which AI adoption far outpaces enforceable regulation; a surveillance accountability deficit exposed by the 2022 Pegasus spyware revelations; multi-agency fragmentation with no single authority holding binding governance power; and a severe research capacity deficit in AI ethics. A comparative analysis with the European Union reveals what the article terms the governance paradox: the country with one of the world's highest AI adoption rates has among the slowest trajectories of governance maturation, a structural challenge with implications for developing economies more broadly. The article further introduces the concept of trust capital to reframe AI governance from a compliance cost to a business sustainability strategy, arguing that organisations investing voluntarily in governance frameworks build compound advantages across transition readiness, ESG credentials, market access, and investor confidence. The article concludes with evidence-based recommendations for policymakers and businesses operating within Thailand's evolving AI ecosystem and the broader ASEAN regulatory environment.



