2026 AI Accuracy & Trust Survey Template

An AI accuracy survey is a structured questionnaire that measures how much professionals trust AI-generated outputs, which error types concern them most — such as hallucinations or outdated training data — and how often they verify results before acting on them in real workflows.

Run this survey after a major AI model release, following a documented hallucination incident in your organization, or at the start of an annual vendor review cycle. Quarterly deployment works well for teams tracking whether confidence in specific tools is rising or falling over time.

The template includes checkboxes for factual claims, recent events, technical details, citations, calculations, compliance guidance, and regional information. Respondents select every category where they have personally encountered unreliable outputs, giving you a ranked breakdown of which failure types cause the most friction.

The hallucination impact radio question asks whether AI errors caused actual problems — not just perceived risk. This separates theoretical concern from documented harm, letting you quantify business impact and build a data-backed case for investing in human review steps or third-party audit requirements.

Respondents rate their verification confidence on a 1–5 scale, where 1 signals they rarely trust outputs without checking and 5 means they rely on AI results with minimal review. This single rating correlates strongly with overall AI adoption readiness and is a high-value signal for AI reliability benchmarking.