Asia Needs Common AI Trust Metrics, Report Warns of Widening Gaps

A new analysis of artificial intelligence (AI) governance across 15 Asian countries, published by the Asia Society Policy Institute (ASPI), has found that while nearly every nation in the region invokes “trust” as central to its AI strategy, none has a reliable or consistent way to measure it. Experts warn that this gap could undermine the continent’s ambitions as it races to harness AI for economic growth. The report proposes nine measurable factors, or metrics, for what it terms “trusted AI ecosystems,” covering areas from data quality and compute infrastructure to misinformation governance and environmental sustainability. The findings are based on policy analysis and two roundtable discussions held during the 2026 AI Impact Summit in New Delhi, involving experts from Australia, Hong Kong, India, Indonesia, Japan, Malaysia, Singapore, South Korea, Sri Lanka, the United Arab Emirates, and the United States. The economic stakes behind the region’s AI push are considerable. UNESCO’s AI readiness assessments suggest that widespread adoption could add up to USD 1.9 trillion to India’s GDP by 2035 and USD 113.4 billion to Malaysia’s economy by 2030. Indonesia’s national strategy frames AI adoption as the path to developed-country status by 2045. Yet, the report finds that this urgency is running ahead of governance. Regulatory frameworks across Asia remain calibrated largely around model-level risks, even as AI development has moved toward agentic systems, autonomous agents that access, combine, and act on data across jurisdictions. The report’s authors warn that governance frameworks unable to measure trust in static deployments are “even less equipped to track it across dynamic, multi-actor agentic architectures.” ASPI’s proposed framework breaks trust down into nine domains. A central argument running through the report is that Asian countries are largely pursuing “sovereign” AI strategies in isolation, competing for investors rather than pooling resources, and often replicating, rather than reducing, their dependencies on external players. The report does not argue that national differences should be erased. Rather, it calls for a common analytical foundation: baseline interoperable principles on safety, accountability, and transparency; mutual recognition pathways for audits and incident response; cross-border data-sharing arrangements; and regular regulator-to-regulator cooperation. Roundtable participants also recommended that rather than constructing new trust indices, policymakers should extract trust-relevant components from existing governance, digital readiness, and cybersecurity indices that are already being collected, but not yet being used to systematically assess trust. “Trust cannot be generated in isolation,” the report concludes, “particularly in economies deeply embedded in global markets and technology dependencies.” Without shared metrics, cross-country comparisons remain abstract, and effective practices continue to be shared on an ad hoc basis, leaving one of the world’s most consequential technology transitions without a common map.