AI-washing
Describing a product or service as using artificial intelligence or machine learning capabilities it does not actually have, or exaggerating the sophistication of the AI it does use, in marketing, filings, or public statements. The term entered regulatory use through the SEC's March 2024 enforcement actions and has since been used by other regulators and journalists to describe the same pattern.
Defined in 4 GAGE programs, which carry 5 distinct definitions of it. The wording above is taught in The AI Lobbyist: Certified AI Policy Strategist.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
Describing a product or service as using artificial intelligence or machine learning capabilities it does not actually have, or exaggerating the sophistication of the AI it does use, in marketing, filings, or public statements. The term entered regulatory use through the SEC's March 2024 enforcement actions and has since been used by other regulators and journalists to describe the same pattern.
Overstating or fabricating an AI capability in marketing or disclosures, claiming a system does something with artificial intelligence that it does not actually do. The gap between the AI claim and the real capability is what regulators target, as the FTC's DoNotPay action and the SEC's first AI-washing settlements (SEC, 2024) both show.
False, overstated, or materially incomplete public claims about a company's use of AI; an oversight failure exposing the company to SEC enforcement and securities claims, controlled at the board level by a verification step before claims are released.
Marketing ordinary software, or ordinary human labor, as artificial intelligence. The reason a buyer must verify what a vendor's "AI" actually is rather than trusting the label. The Builder.ai collapse is the extreme case.
Misrepresenting or overstating an AI system's actual capabilities, particularly in investor-facing or consumer-facing claims; the SEC has brought enforcement actions on this theory (SEC v. Delphia and SEC v. Global Predictions, 2024).
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Board-Level AI Governance · Bonus: AI Leadership Accelerator, Certified AI Practitioner: Workplace Foundations
- Answering a regulator's letter: responding with documents, not assurances, anchored to real enforcement patterns · The EU AI Act: The Executive Map, Certified AI Governance Professional (CAIGP)
- Bullshit Detection: Red Flags That Someone Is Technically Bluffing · The Point Person Mandate, The AI Lobbyist: Certified AI Policy Strategist
- The Liability Risk Assessment and Mitigation Strategy · Legal Frameworks and Liability Navigation, The AI Lobbyist: Certified AI Policy Strategist
- Build vs Buy vs Partner · Technology, Platforms and Vendors, Certified AI Transformation Professional (CATP)
Where it shows up at work
A definition is where AI-washing starts. The lessons above teach it inside the competencies below, which are what job descriptions ask for and what the GAGE credential records. Every link here is drawn from the same careers map that builds a role's readiness check.
Designs decision rights, committees, intake, approval tiers and escalation so routine uses move and consequential uses get reviewed.
One lesson on this page teach it as a primary outcome.
Turns technical uncertainty into a one-page decision: material risks, trends, exceptions, remediation, and what the board is being asked to accept.
One lesson on this page teach it as a primary outcome.
Reviews purpose, data, affected people, accuracy, bias, security, oversight, vendors and law for a use case, scores likelihood and impact, and documents residual risk.
One lesson on this page teach it as a primary outcome.
Roles that hire for it
Each role page shows the full competency set, what the seat decides, and a readiness check against your own evidence.
- Chief AI Officerneeds it at depth
- AI Governance Managerneeds it at depth
- Chief Risk Officer, AI risk editionneeds it at depth
- VP of AI Governance and Ethicsneeds it at depth
- Chief Compliance Officer, AI compliance editionneeds it at depth
- Autonomous Systems Governance Lead, robotics and physical AI editionneeds it at depth
How job descriptions say it
Postings rarely use the textbook word. These are the phrases the careers map reads as asking for the competencies above.
Where the frameworks place it: NIST AI RMF GOVERN; ISO/IEC 42001 Clause 5; NIST AI RMF MAP and MEASURE; ISO/IEC 42005.
One interview question about it
Sketch the governance operating model you would set up for a company deploying its first customer-facing AI. Who decides, who reviews, and who can stop it?
Asked of candidates for ai governance operating model design. Answering it in your own words is exactly how a GAGE topic is passed, and the credential records the pass where an employer can check it.
If you come from another field
Some backgrounds already carry this competency, and the readiness check gives credit for it.
- Internal audit and IT audit carries it as a claim to back up: Audit committee reporting is part of senior audit roles.
- Nonprofit program and grants oversight carries it as a claim to back up: Board and funder reporting is the cadence a governance committee needs.
- A business, MBA or technology management degree carries it as work you can show: Executive briefs and presentations are your assignments.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.