AI claim risk phrases that carry high evidence burden
Last reviewed June 2, 2026
These are not banned terms. Each phrase below represents a claim pattern that requires specific evidence before a buyer can rely on it. When an AI vendor uses this wording without the corresponding evidence, that is an evidence signal — not a verdict about the company.
Nine patterns that need evidence
Evidence burden level reflects support needed and wording risk — not legality, compliance status, or purchasing safety.
"Fully automated""No human review needed""End-to-end automation" - Evidence needed
- Task scope definition, human oversight steps, escalation protocol, failure handling, and which tasks still require a human decision.
- Buyer question
- Which tasks still require human review or escalation, and what triggers that handoff?
- Source basis
- FTC accessiBe final order (2025) · SEC Presto Automation order (2025)
"98% accurate""Human-level accuracy""Outperforms experts" - Evidence needed
- Benchmark dataset, content types covered, model version tested, sample size, false-positive and false-negative rates, and whether the test matches your actual workflow.
- Buyer question
- Does the accuracy figure hold for the document types and volume in your specific workflow?
- Source basis
- FTC v. Workado complaint (2025) · NIST GenAI text-to-text evaluation (2024)
"Bias-free AI""Zero bias""Fair AI""Equitable model" - Evidence needed
- Subgroup performance breakdown by demographic group, false-positive and false-negative rates per group, training-data coverage, and deployment conditions under which fairness was measured.
- Buyer question
- What subgroup performance data is available, and were the test conditions representative of your deployment setting?
- Source basis
- FTC v. IntelliVision (2024) · NIST AI RMF 1.0 · ICO AI fairness guidance
"HIPAA compliant AI""GDPR-safe AI""Meets regulatory standards" - Evidence needed
- Framework scope, covered controls, audit or assessment method, customer responsibilities, exclusions, and whether a BAA or DPA is required.
- Buyer question
- Does this cover your deployment configuration, data flows, and sub-processor chain — or just the vendor's own infrastructure?
- Source basis
- HHS/OCR HIPAA guidance · EDPB Guidelines on Automated Decision-Making · GDPR Art. 22 & 35
"Guaranteed ROI""Cut costs by 80%""10× cost savings" - Evidence needed
- Customer outcome distribution (median and percentile range, not just top performers), baseline and measurement-period definition, cohort definition, cost basis, and attribution methodology.
- Buyer question
- What does the full distribution of customer outcomes look like, and which customers are excluded from the headline figure?
- Source basis
- FTC v. Air AI complaint (2025) · FTC business guidance on AI claims
"AI-powered""AI-native""AI-driven""Agentic AI" - Evidence needed
- What the AI specifically does, what input it processes, what output it produces, how it differs from a non-AI version, and what human oversight is involved.
- Buyer question
- What specific task does the AI component perform, and what does the non-AI fallback path look like?
- Source basis
- ASA/CAP AI as a marketing term report (2024)
"Replaces lawyers""No agent needed""AI does the work of 10 people" - Evidence needed
- Task scope, which tasks still require professional oversight, escalation protocol, and when the vendor recommends involving a qualified professional.
- Buyer question
- For which tasks does the vendor still recommend or require professional review, and how is that escalation triggered?
- Source basis
- FTC v. DoNotPay final order (2025)
"First AI to...""Only platform that...""Industry-leading AI""Most advanced" - Evidence needed
- Market scope definition, comparison methodology, point-in-time reference when the comparison was checked, and evidence that no prior comparable offering existed.
- Buyer question
- What comparison set was used to establish this claim, and when was it last checked against alternatives?
- Source basis
- SEC v. Delphia & Global Predictions (2024)
"Enterprise-grade security""SOC 2 AI""Secure by design" - Evidence needed
- Audit scope and SOC 2 type, certification date, which data flows are in scope, third-party audit report availability, and known exclusions or customer-side requirements.
- Buyer question
- Which SOC 2 criteria are included and which of your data flows — including sub-processors — fall within the audit scope?
- Source basis
- FTC guidance on substantiation of technical security claims
AI claim risk phrase questions
- Are these banned AI claim phrases?
- No. They are wording patterns that carry higher evidence burden. A buyer should ask what evidence supports the exact phrase, what scope limits apply, and whether a narrower wording boundary would be more accurate.
- How should I use this AI claim risk phrases checklist?
- Find the closest phrase pattern, read the evidence needed, then paste the vendor's exact wording into the checker. The checker reviews the specific claim language and returns evidence needed, buyer questions, and wording boundaries.
- Which AI claim phrases should be checked first?
- Start with phrases that imply broad accuracy, full automation, compliance coverage, ROI certainty, no bias, hallucination-free output, or first/only/best status. Those claims usually need the most specific evidence before a buyer can rely on them.