2026 AI Accuracy & Trust Survey-0

2026 AI Accuracy & Trust Survey

Do you actually trust what AI tells you?

Hallucinations, outdated training data, confident-sounding errors — AI accuracy concerns are among the top reasons people hesitate to fully rely on AI tools. This survey measures real trust levels, verification habits, and where accuracy concerns are holding AI adoption back in 2026.

Anonymous. Takes 3 minutes.

What is your role?

Industry

Overall, how much do you trust AI-generated content or answers to be accurate?

Very high trust — I rarely verify

Moderate trust — I spot-check important claims

Low trust — I verify most AI output

Very low trust — AI is a starting point only

I don't use AI tools

In which contexts do you most often catch AI errors? (Select all that apply)

Factual claims and statistics

Recent events (after training cutoff)

Technical or domain-specific details

Citations and source references

Numerical calculations

Legal, medical, or compliance information

Local or regional information

How often do you verify AI-generated facts before using them?

Always — every factual claim

Usually — when it matters

Sometimes — for high-stakes content only

Rarely

Never — I trust the output

Has an AI hallucination ever caused a real problem for you or your team?

Yes — a significant incident

Yes — minor issues a few times

Not yet, but I've caught errors before they caused harm

No — never encountered a meaningful error

I don't know — may have happened without realizing

Which AI tools do you consider most accurate and reliable?

Claude (Anthropic)

ChatGPT (OpenAI)

Gemini (Google)

Perplexity

Microsoft Copilot

They're all about the same

None are reliable enough to trust

How has your trust in AI accuracy changed over the past 12 months?

Increased — the models have improved

Stayed about the same

Decreased — more aware of errors now

Mixed — better in some areas, worse in others

What would most increase your trust in AI output? (Select all that apply)

Real-time web access with source citations

Confidence scores on statements

Clearer disclosure when the model is uncertain

Domain-specific fine-tuned models

Human review layer before output is shown

Third-party accuracy audits of AI tools

Rate how confident you feel using AI output without independent verification

Describe a situation where AI accuracy (or inaccuracy) had a real impact on your work.

Email (optional — to receive the published report)

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