Which AI claim type are you looking at?

FTC AI claims

How FTC substantiation standards apply to AI accuracy, outcome, and automation claims in marketing copy.

SEC AI washing

AI use and performance wording from SEC source examples. Use as source context, not investment advice.

EU AI Act transparency claims

Transparency, AI disclosure, and handoff wording under EU AI Act source context, with buyer questions for public AI product claims.

AI claim substantiation

Map AI accuracy, compliance, bias, and automation wording to the evidence a buyer should request.

Walk one vendor page or claim set

Step-by-step evidence checklist for a single vendor page or pasted claim set—not a full procurement review.

AI accuracy claims

Accuracy and performance wording checked against field evidence, benchmark scope, subgroup results, and testing limits.

AI detector accuracy claims

Numeric accuracy, benchmark scope, false positive / false negative rates for AI detection tools.

AI support agent resolution and accuracy claims

Resolution-rate, deflection, hallucination, handoff, and accuracy wording on support-agent pages, with buyer evidence questions.

Bias-free AI claims

Bias-free and fairness wording, with questions about tested groups, error rates, monitoring, and limits.

AI ROI and cost-saving claims

AI revenue, savings, productivity, and outcome wording checked against customer result distribution and cost basis.

AI chatbot and LLM accuracy claims

When an AI assistant or LLM claims professional-level output, this guide shows what task scope, qualified comparison, and failure-condition records to ask for.

"First," "only," or "best" AI claims

Uniqueness and superlative AI claims checked against market scope, comparison set, and point-in-time evidence.

AI-powered meaning

Vague AI-powered, AI-native, built-in AI, and agentic AI descriptors mapped to workflow evidence and buyer questions.

AI replacement claims

Professional-replacement and no-human-needed AI claims, with questions about task scope, testing, and review boundaries.

Fully automated AI claims

Fully automated and no-human-review wording, with questions about edge cases, escalation paths, and review limits.

AI washing examples

Common vague and overstated AI claim patterns with evidence gaps, evidence signals, and wording boundaries.

Human review boundary claims

Expert-reviewed, human-in-the-loop, handoff, and oversight wording—what evidence buyers should request when a claim implies human involvement without defining it.

HIPAA-compliant AI claims

Healthcare AI privacy and security wording, with buyer questions about vendor role, data flow, safeguards, and scope limits.

Secure AI assistant claims

Security and private-by-design AI assistant wording, with questions about data retention, admin controls, model access, and safeguards.

AI hiring and screening tool claims

When an AI hiring tool claims fair, objective, or consistent evaluation, this guide shows what bias audit records, candidate disclosure, and FCRA evidence to ask for.

High-burden AI marketing wording

Spot high-evidence-burden phrases in public AI marketing copy and map each pattern to evidence buyers should request.

ASA/CAP AI advertising claims

When an AI ad uses vague AI-powered wording, no-limits creative claims, or companion positioning, this guide shows what substantiation ASA and CAP expect.