Organizations that adopt trustworthy AI practices are 15 times more likely to report strong returns on their AI investments, according to a new SAS report developed with research insights from IDC.
The second annual Data and AI Impact Report: The New Economics of Trust found that organizations with stronger AI governance, data quality, explainability and auditability consistently achieved better business outcomes. These organizations reported at least twice the ROI of peers, while fewer than one in 20 AI-trust laggards reported comparable returns.
The findings also highlight the growing importance of trust as AI systems become more autonomous. Generative AI earned a 76% trust level compared with 66% for agentic AI, while 97.2% of users said they override AI-generated recommendations in at least some situations. The leading reason for overrides was an AI system’s inability to explain its decision.
Southeast Asia accelerates AI adoption
Southeast Asia, represented in the study by Singapore, Malaysia and Thailand, was the only market to exceed global benchmarks across all measured dimensions of AI trustworthiness.
The region’s share of organizations describing their AI programs as integrated or transformative rose from 52.5% in 2025 to 73% in 2026. Agentic AI adoption also increased from 39.2% to 51.6%.
However, data infrastructure remains a challenge globally. Only 17.5% of enterprises have a fully optimized data infrastructure considered mature enough for agentic AI. Organizations with optimized data foundations were four times more likely to expect strong AI ROI.
The report is based on a survey of 2,699 decision-makers across 28 countries, covering banking, insurance, life sciences and the public sector.
SAS identifies five core dimensions of trustworthy AI: data quality and governance, model governance and oversight, explainability and fairness, responsible AI policy, and audit and accountability.
