When AI Makes It Up: Real Risks of Hallucinations Every Exec Should Know
Artificial intelligence (AI) models are getting smarter—but they’re also getting bolder in their mistakes. These errors, known as hallucinations, happen when AI confidently generates false or fabricated information. And unfortunately, it’s an issue that doesn’t seem to be getting better as technology advances. In fact, a New York Times report found that “the newest and most powerful technologies […] are generating more errors, not fewer.”
In regulated industries or high-stakes decisions, that’s more than a nuisance—it’s a liability. We asked members of the Senior Executive AI Think Tank to share one real-world consequence of AI hallucination that every executive should understand. Their insights show how quickly an unchecked output can unravel trust, decision-making and business reputation.
“AI hallucinations can severely undermine customer trust and brand reputation.”
False Outputs, Real Consequences
Sarah Choudhary, CEO of Ice Innovations, puts it plainly: Hallucinations are a direct threat to trust.
“When a model confidently presents fabricated information, it can lead to critical errors in decision-making, financial loss or even regulatory penalties,” she warns. In industries like healthcare, finance or legal services, hallucinations can have especially high-stakes consequences.
Her advice? “Every AI implementation needs human-in-the-loop validation and rigorous oversight to protect brand integrity.”
Trust Isn’t Transferable
Jim Liddle, Chief Innovation Officer at Nasuni, explains that hallucinations don’t just look bad—they feel real.
“One false product recommendation or legal citation can destroy trust that took years to build,” he says. “Customers don’t distinguish between ‘The AI got it wrong’ and ‘Your brand published false information.’ It’s your credibility on the line.”
Don’t assume outputs are right just because they’re confident. Build in verification.
Hallucinations Can Invite Legal Trouble
Roman Vinogradov, VP of Product at Improvado, points to recent cases where AI-generated case law made it into court filings, resulting in sanctions.
“It’s not just embarrassing—it’s reputational damage, public scrutiny and in some cases, legal risk,” he says. “For execs, the lesson is simple: AI outputs must be validated, especially in high-risk domains.”
“AI hallucinations can lead to significant financial loss and reputational damage.”
Financial Fallout from Bot Mistakes
Nikhil Jathar, CTO of AvanSaber, references a headline-making case: An Air Canada chatbot gave incorrect refund information, and the airline had to honor it in court.
“That one hallucination cost real money,” he says. “Now imagine a bot giving the wrong investment advice or compliance guidance. The reputational and financial impact is real.”
The Slow Decline of Critical Thinking
For Daria Rudnik, CEO of Aidra.AI, the danger is deeper than just bad data.
“When teams rely on AI without scrutiny, they gradually lose the habit of thinking critically,” she says. “Hallucinations aren’t just misinformation—they’re a symptom of disengagement.”
Her advice? Make AI collaboration, not dependence, the goal. “The best decisions still require human judgment.”
Misleading Advice Erodes Brand Credibility
Egbert von Frankenberg, CEO of Knightfox App Design, underscores how convincingly false information can spread.
“Incorrect product details or bad advice from a bot damages brand credibility immediately,” he says. “You need validation tools, monitoring and a plan for what happens when things go wrong.”
“I once asked AI to help write a job description for an entry-level cybersecurity role. It required a degree plus 5–7 years’ experience. No surprise—no one applied.”
Invisible Errors in Hiring and HR
Gordon Pelosse, EVP at AI CERTs, shares a subtler example: AI hallucinating in job descriptions, raising questions about how to ethically implement AI in HR.
“I once saw an AI recommend a degree and 5–7 years of experience for an entry-level role,” he explains. “No one applied.”
His point? “Hallucinations don’t always cause PR crises—but they quietly undermine efficiency and equity if left unchecked.”
It’s Not Just a Glitch—It’s a Fault Line
Divya Parekh, Founder of The DP Group, says the problem isn’t that hallucinations happen. It’s how little they’re recognized for what they really are.
“Hallucinations aren’t tech bugs. They’re cracks in the credibility your business stands on,” she says. “One false quote, one fake citation, and trust shatters. Precision is the price of reputation.”
Action Steps for Leaders in AI
- Assume every confident AI output might still be wrong. Don’t confuse fluency with accuracy.
- Implement human validation. This is especially key for anything customer-facing, legal or regulatory.
- Train teams to think with AI, not follow it blindly. Critical thinking is a competitive advantage.
- Monitor and audit AI systems. Have a plan for error detection, escalation and correction.
- Be transparent when mistakes happen. Owning errors quickly can protect your credibility.
What Executives Can Do When AI Gets Things Wrong
AI hallucinations aren’t future hypotheticals—they’re happening now, and they’re hitting everything from customer service to legal filings. Worse, most experts agree that the issue of hallucinations “isn’t fixable.”
When things go wrong, it’s your name—not the AI model’s—that people remember. The solution is in using AI wisely. Executives must lead with a blend of tech adoption and human oversight, treating hallucinations not as flukes but as warning signs. Because in a world increasingly built on AI outputs, trust is your most valuable asset—and the hardest to earn back.
