GTM Assurance

AI-Claims Audit

Checking whether your "AI-native" claim holds up, before an investor or regulator calls it AI-washing.

If an investor or a journalist asked you to prove the AI claim on your homepage, could you?

Research from MMC Ventures found that 40% of companies labelled "AI startups" in Europe showed no real evidence that AI was material to their business at all. The label was marketing, not fact.

That gap has a name now: AI-washing, sometimes written AI washing. It means a company overstates what its AI actually does, or how central it is to the business. Regulators have started to treat it as misrepresentation: in March 2024 the US SEC settled its first AI-washing cases, against two investment advisers, Delphia and Global Predictions, with combined penalties of $400,000 (SEC press release). Investors, boards, and increasingly journalists now check for it before they take a growth story at face value.

This audit does that checking in advance: a plain read of what your product, marketing, and GTM claims actually say about AI, against what's really happening underneath.

How This Works

Here's What This Actually Looks Like

A line-by-line read of where AI claims show up, product copy, pitch deck, website, marketing, and whether each one is backed by something real.
Flagging claims that are technically true but easy to misread as more than they are, a vendor's AI feature presented as the company's own capability, for instance.
A plain-language rewrite for any claim that's currently exposed, so the real capability is represented honestly and still sounds credible.
Done quietly, before an investor, acquirer, or reporter raises it first.

This sits next to the newsletter work I do on the same topic, The Silent Noise has an issue planned that looks at how easy it's become to spot a hollow "AI-native" resume claim from the hiring side. This audit is the same lens, turned on a company's own claims instead.

It also runs as a standard check inside my GTM Due Diligence for Investors work, for any target company whose pitch leans on an AI narrative. As a standalone service, it's for a company that wants that same check run on itself, before someone else runs it for them.

Good fit if:

your growth story leans on an AI claim, and you want it checked before an investor, acquirer, or reporter does.

Not a fit if:

you need the AI itself built or audited for technical performance. This checks what's claimed against what's real, not model accuracy or infrastructure.

Frequently Asked

FAQs: AI-Claims Audit

What is "AI-washing"?

Claiming AI capability a product doesn't meaningfully have, or overstating how much of a result AI is actually responsible for. It's increasingly how investors and journalists describe hollow AI claims.

How do you check this?

A direct read of where AI shows up in your claims, then a conversation with your team about what's actually happening underneath each one.

What if you find a real problem?

You get a plain-language rewrite for the exposed claim, and a chance to fix it quietly, before anyone outside the company raises it.

Is this only for companies that call themselves "AI-native"?

No. Plenty of companies make a narrower AI claim, in one product line or one piece of marketing, that's worth checking the same way.

Will you tell my investors if something doesn't hold up?

No. This is between you and me. What you do with the findings is your call.

How is this different from GTM Due Diligence for Investors?

That service runs this same check on someone else's company, for a fund or acquirer. This runs it on your own, before that evaluation happens.

See General FAQs

Worth Knowing

“40% of companies labelled 'AI startups' in Europe showed no real evidence that AI was material to their business.”

The label was marketing, not fact, and the gap now has its own name: AI-washing. It's exactly what investors, boards, and increasingly reporters are starting to check for.

Source: MMC Ventures, "The State of AI 2019: Divergence"

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higaurav@gauravbhattnagar.com

AI-Claims Audit

Here's What This Actually Looks Like

Good fit if:

Not a fit if:

FAQs: AI-Claims Audit

Book a Free Discovery Call

Thirty minutes, no pitch.

Book a Free Discovery Call

Prefer to Write First?

Gaurav Bhatnagar

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