Governance Determinants of AI-Enabled Mental Health Systems in LMICs

Digital and AI-enabled tools are increasingly integrated into mental health systems in low-and middle-income countries to address treatment gaps. While clinical effectiveness and ethical principles have received attention, structural governance determinants influencing equity, accountability, and system integration remain less systematically examined. We conducted a structured policy and literature analysis (2015–2025) of AI-enabled mental health deployments in LMICs, analyzing 78 peer-reviewed publications and policy documents using best-fit framework synthesis. Governance-relevant patterns were coded across accountability mechanisms, data governance, infrastructural inclusion, and cultural validation. Across cases, four recurring patterns emerged: limited post-deployment monitoring of algorithmic performance; data governance framed as privacy compliance rather than structural stewardship; infrastructural access constraints affecting participation; and variable attention to cultural validation beyond translation. These findings suggest implementation outcomes are shaped not only by clinical effectiveness but by governance arrangements. Clarifying these governance domains may support more systematic integration of digital tools within mental health systems, though empirical validation in prospective studies is warranted.