Fake deals created by AI are causing headaches for food businesses
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At a family-run pizzeria in Wentzville, Missouri, misinformation is not coming from a competitor or an online prank but from artificial intelligence. Stefanina’s Pizzeria has faced a wave of frustrated customers demanding nonexistent specials and invented menu items. These errors, generated by AI-driven summaries on the web, show how digital inaccuracies affect small businesses that rely on customer trust.
How fake deals are created by AI search summaries
Customers have walked in insisting on promotions that never existed. Some were told by AI-generated listings that a large pizza could be purchased at the price of a small, while others expected “buy one, get one free” offers the restaurant never introduced. The owners clarified the situation with a public statement, but not before staff endured hours of explaining and calming unhappy guests. A post on the restaurant’s Facebook page warned customers against trusting specials listed online, stressing that these were fabrications beyond their control.
The inaccuracies highlight a larger challenge: AI-driven summaries sometimes treat incomplete or mismatched data as fact. For Stefanina’s, the consequences quickly moved from online confusion to in-person confrontation.
The business impact of misinformation on small restaurants
For a small, family-owned operation, each misunderstanding means wasted staff time, reduced efficiency, and strained customer interactions. Unlike large chains with corporate communications teams, local businesses rarely have the capacity to absorb the fallout. Angry customers not only leave without ordering but often share their dissatisfaction online, extending the damage further.
Restaurant owners also face the choice of whether to honor fake deals at a financial loss or risk upsetting customers by refusing. Either way, their reputation is at stake, and the disruption threatens the bottom line.
Understanding AI hallucinations and why they matter
The phenomenon behind these false specials is known as an AI hallucination. This occurs when artificial intelligence generates answers that sound authoritative but are not grounded in factual data. Hallucinations are not rare; they stem from limitations in the data used to train AI models, as well as the way those models predict language.
The issue has cropped up elsewhere. Earlier this year, AI-generated summaries suggested adding glue to pizza to improve cheese stickiness. While humorous, the underlying risk is clear: if consumers trust AI summaries without checking, businesses bear the fallout of mistakes they did not cause.
For industries like hospitality and food service, where consumer decisions are often immediate, the consequences of an AI hallucination can play out at the counter within minutes.
Expert warnings and strategies to fight back
AI experts argue that this problem stems from overreliance on automated answers. Jonathan Hanahan, a professor at Washington University, has noted the distinction between using AI and working with AI. He cautions that prompts and verification matter, and without skepticism, hallucinations slip through unchecked.
For small businesses, the most effective defense lies in communication. Posts on social media, website updates, and signage in stores can alert customers to potential inaccuracies. Another safeguard is ensuring official business listings are continuously updated and verified, reducing the chances of AI tools pulling outdated or incorrect data. While such steps require time, they provide a defense against reputational harm.
The challenges faced by Stefanina’s raise a larger question about responsibility in the AI era. As these systems increasingly shape public perception, small businesses stand exposed to risks they cannot control. Restaurants, repair shops, and local retailers may find themselves correcting digital errors just as often as they serve customers.
Until stronger safeguards and more accurate AI systems emerge, small businesses will need to invest in vigilance and customer communication. The case in Missouri may seem like an isolated inconvenience, but it represents a broader reality: AI-generated content, while convenient, is still prone to mistakes, and the cost of those mistakes often falls on the people least equipped to handle them.