What percentage of decision-makers trust agentic AI?

Only 66% said they trust agentic AI, compared to three-quarters who trust generative AI more broadly.

Why do respondents override AI decisions?

The top reason was insufficient explanation of how the AI reached its answer, cited more than twice as often as the output simply being wrong.

AI Business & IndustryAI Safety & AlignmentSemafor Tech4d agoSep 3, 2026, 06:00 JST1 min read

AI rollout outpaces trust in businesses, study finds

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3 Key Points

What happened
A SAS survey of 2,700 decision-makers across 28 countries found that nearly 90% say AI agents play some decision-making role in their organizations. Only 66% trust agentic AI, while three-quarters trust generative AI more broadly.
Why it matters
The gap shows businesses are deploying AI faster than they trust it, which could limit adoption. The main reason for overriding an AI’s decision was insufficient explanation—cited more than twice as often as the output being wrong.
What to watch
The top reason for overriding decisions highlights a need for better explainability in AI systems. The survey suggests trust may grow as AI provides clearer reasoning for its choices.

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Context & Analysis

The survey, commissioned by SAS and covering 2,700 decision-makers in 28 countries, reveals a tension between rapid AI adoption and employee confidence. While nearly 90% of organizations involve AI agents in decision-making, only two-thirds trust them fully. This gap may slow further rollout unless companies address explainability. The finding that poor explanations are the primary reason for overriding AI decisions suggests that improving transparency could be more effective than improving accuracy alone. For non-technical leaders, the takeaway is that investing in AI that clearly communicates its reasoning might build the trust needed to unlock its full value.

FAQ

What percentage of decision-makers trust agentic AI?: Only 66% said they trust agentic AI, compared to three-quarters who trust generative AI more broadly.
Why do respondents override AI decisions?: The top reason was insufficient explanation of how the AI reached its answer, cited more than twice as often as the output simply being wrong.

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