AI Washing: How to Spot It in Supplier Claims

If you’ve ever come across “greenwashing” (when companies exaggerate their eco-credentials to appear sustainable) or 'pinkwashing' (when companies, governments, or organisations promote themselves as LGBTQ+-friendly, but do little to support LGBTQ+ rights in reality) - you already understand the idea behind AI washing. It’s the same tactic, but with technology.

In our previous blog, about the importance of AI performance metrics, we discussed how the U.S. Federal Trade Commission launched Operation AI Comply to combat AI Washing, and the UK’s Advertising Standards Authority (ASA) issued rulings on misleading AI claims.

AI washing happens when suppliers overstate, mislabel, or exaggerate their use of AI to make their product sound more innovative, competitive, or trustworthy than it really is. And right now, it’s everywhere.

In fact, AI has become such a buzzword that it shows up in tenders and supplier pitches where there’s little to no actual machine learning behind the scenes. For procurement professionals, this creates a real challenge: how do you tell the difference between genuine innovation and marketing hype? It's all about smart supplier due diligence!

Why AI Washing Matters for Procurement

AI washing isn’t just harmless exaggeration. For buyers and procurement teams, it carries very real risks:

• Cost risk: paying a premium for “AI-powered” tools or those positioned as proprietary when they are actually just off the shelf or rules-based automation.

• Performance risk: systems that overpromise often underdeliver in real-world settings.

• Compliance risk: regulators in the UK, EU, and healthcare sector are increasingly scrutinising AI claims - and passing that risk down the supply chain.

• Reputational risk: adopting “AI-washed” tools can erode trust with stakeholders and service users if the technology doesn’t stand up to scrutiny.

Red Flags to Watch Out For

Procurement or compliance professionals don’t need a technical background to spot AI washing. The warning signs are usually clear once you know what to look for in your vendor assessments:

• Vague claims like “AI-driven insights” or “smart automation” with no detail behind them.

• No evidence of training data, model performance metrics, or independent validation.

• “Black box” responses when you ask how the system makes decisions.

• Reluctance to explain whether or how humans remain in the loop for critical processes.

Questions Every Buyer Should Ask

The best way to cut through AI washing is to build direct, practical questions into your tender process and contract management activities. Any supplier making genuine use of AI should be able to answer these clearly.

1. What exactly does your AI do that a rules engine or database couldn’t?

2. What data is it trained on, and how often is it updated?

3. Can you show performance metrics (accuracy, error rates) in a procurement-relevant context?

4. What off-the-shelf models feature in the system pipeline?

If a supplier can’t answer these questions, or avoids them, that’s your signal to push harder, or to move on.

At Kafico, we work both as governance consultants and as providers of an AI procurement platform (CLEAN AI). From that vantage point, we’re seeing AI washing become a common feature in supplier claims. The good news is: procurement teams don’t need specialist knowledge to protect themselves.

With the right flags and the questions, it’s possible to separate genuine innovation from marketing hype, and make sure you’re paying for real value.

This post is the first in our series on AI risks in procurement. Next time, we’ll look at the other side of the coin: AI laundering; when suppliers deliberately disguise the presence of AI in their system pipelines.

We’ll also be exploring these themes at our December event, Scrutinising AI Systems Effectively. Save the date if you want practical tools for challenging supplier claims and making confident buying decisions.

Emma Kitcher, Founder of CLEAN AI: a snazzy new AI procurement platform