Theranos whistleblower Tyler Shultz has warned that the AI boom is ‘a great opportunity to go deceive people’, arguing that investors now struggle to tell genuinely new technology from products that merely repackage existing models.
Shultz, whose first job after college was at Theranos and who helped expose its dangerously inaccurate blood-testing devices, made the remarks in an interview with The San Francisco Standard, reported by TechCrunch on 30 October 2026. The interview followed the documentary ‘You Can See Everything’, about Theranos founder Elizabeth Holmes in her final weeks before prison.
The warning, in his words
‘A huge danger with AI is that I think it is really hard to do due diligence on it,’ Shultz said. ‘It’s really hard to tell the difference between what is something truly unique and new versus like, a ChatGPT wrapper… If you want to deceive people, I think this is a great opportunity to go deceive people.’
He did not name any AI company or allege a specific fraud. His point is about diligence, not an accusation: when a system is complex, an investor cannot easily verify what a team actually built versus what third-party models and services provide.
Why Theranos is the reference point
Theranos reached a peak valuation of around $10 billion despite its technology never working as claimed — using its own machines for only a fraction of tests and outsourcing the rest to third-party equipment, while faulty results reached real patients through Walgreens stores. Holmes was convicted in January 2022 of one conspiracy count and three counts of investor fraud, and is in federal prison.
Shultz’s argument is that the lesson is being forgotten just as unprofitable AI companies raise capital at trillion-dollar valuations. ‘I think the days of having a thirty-minute coffee with someone and sending them $100,000 should be over,’ he said. ‘Elizabeth took that model and scaled it to $100 million.’
What this does and does not claim
Shultz is describing a risk, not predicting that any particular AI company is a fraud. A product built on an existing model can still be useful, and a novel product can still fail. The test he implies is evidence: what the team built itself, what it can demonstrate, and what independent checks confirm — rather than a founder’s story or a funding round.
For readers, the practical takeaway is narrower than the headline: ask what is new, what is borrowed, and what has been independently verified before treating a valuation as proof of a breakthrough.
Sources
- TechCrunch — Theranos whistleblower Tyler Shultz warns that the AI boom is ‘a great opportunity to go deceive people’
- TokenPost — Theranos Whistleblower Warns AI Boom Could Create Room for Deception
- NewsBytes — Theranos whistleblower Tyler Shultz warns investors about AI hype
