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Food businesses and delivery platforms face rising threat from AI-fabricated claims
Key takeaways
- AI-generated images and AI-written complaints emerge as new tools for food fraud, making it harder for hospitality businesses to verify customer claims.
- Fraudulent complaints can carry significant financial and regulatory consequences, from refund costs to potential Environmental Health Officer investigations.
- Industry experts say robust complaint management processes, staff training, and detailed record-keeping will be critical as AI-generated evidence becomes increasingly convincing.

Hospitality businesses are being warned to prepare for a growing form of fraud involving artificial intelligence, as food safety specialists report an increase in complaints supported by AI-generated images and legally worded correspondence designed to secure refunds and compensation.
According to UK food safety and compliance consultancy Food Alert, operators are increasingly encountering manipulated images that appear to show mold, foreign objects, or undercooked food, alongside sophisticated complaint emails generated using AI tools.
The consultancy says the trend is creating new financial and reputational risks for restaurants, takeaways, and foodservice operators already navigating rising operational costs and heightened scrutiny around food safety standards.
Food Alert’s advisory team reports that fraudulent complaints are becoming more convincing as AI technology advances. The business has identified two key emerging threats: fabricated photographic evidence and AI-written intimidation tactics.
Advances in AI bring new threats
Speaking to Food Ingredients First, Annabel Kyle, technical director at Food Alert, explains that AI-generated food fraud is currently an emerging threat rather than an endemic one. She warns that technology is evolving rapidly and is likely to become a far more significant challenge for F&B businesses in the near future.
The issue is particularly significant for businesses operating through food delivery platforms, where complaints can sometimes trigger automatic refund processes before the cost is passed back to operators.
“The trend hasn’t yet fully scaled, but all the necessary ingredients are there: the tools are free, the execution is simple, and the financial incentive on digital platforms that process refunds automatically is obvious. We are primarily seeing this emerge on Twitter and Reddit forums, where users share prompt templates and generated images to encourage others to target delivery aggregators,” says Kyle.
“The broader data demonstrates just how quickly access to this tooling has exploded. AI image editing quickly became the fastest-growing software category of 2024, growing 441% year over year. Ultimately, the barrier to creating a highly convincing food image has plummeted from requiring a professional photographer to just a free account and 30 seconds.”
Bad actors target restaurants and food delivery
While the scale of the problem is still difficult to quantify, Kyle says clear patterns are beginning to emerge in how AI is being used to support fraudulent claims.
“With AI-edited product images, bad actors can manipulate food to appear visually different from what was actually delivered, simulating undercooked meat, contamination, or foreign bodies that were never present. Alongside this, AI-assisted complaint letters utilize large language models to produce highly structured, fluent correspondence. This text mimics an experienced consumer advocate and frequently threatens regulatory escalation.”
AI-generated images and complaint letters are creating new fraud risks for restaurants and food delivery businesses.
While AI-generated text can often still be identified through language patterns, Food Alert believes image manipulation presents a greater challenge and is likely to become increasingly difficult to detect as technology develops.
The consultancy argues that existing legislation has not yet caught up with AI-enabled fraud in this area, leaving businesses with limited protection against fabricated evidence.
“Genuine complaints tend to be informal, emotionally driven, and highly specific to what the individual actually experienced. They typically escalate organically based on how a business handles the initial outreach. AI-assisted coercion starts entirely differently. The very first message is already rigidly structured, heavily legally referenced, and explicitly threatening. Before any dialogue has taken place, regulatory bodies are cited, legal action is mentioned, and social media exposure is flagged,” Kyle explains.
“Furthermore, the claims are often sweeping and maximally harmful, yet completely short on personal narrative or a clear timeline of events. However, it is worth noting that a genuine customer may also use AI simply to draft a better letter. Tone alone isn’t the ultimate test. The true indicator is often the complete absence of verifiable, specific detail.”
The concern is not simply that AI-generated images exist, but that they are becoming convincing enough to undermine traditional methods of complaint verification.
Kyle points to research highlighting how difficult AI-generated food imagery has become to detect. In a 2025 consumer study, most participants failed to distinguish AI-generated versions of common dishes from genuine photographs, raising concerns about how complaint handling teams can reliably verify images under time pressure.
Deepfake detection
Food Alert advises businesses to watch for tell-tale signs of AI manipulation. In images, this can include inconsistent lighting, unnaturally perfect textures, distorted hands and fingers, or backgrounds featuring repeated patterns and impossible geometry.
“Developing a healthy skepticism toward unusually polished first-contact communications is a trained skill. Food Alert teams utilize security awareness training from KnowBe4, which includes dedicated deepfake detection content to hone these exact pattern-recognition instincts,” Kyle tells us.
As AI makes fake food-safety evidence more convincing, hospitality operators are strengthening complaint management and fraud detection processes.
From a technical perspective, the gap between what the technology can execute and what enforcement infrastructure can detect is currently very wide, and it isn’t closing quickly. The detection infrastructure remains poor.
“Only 38% of AI image generators implement adequate watermarking, and a mere 18% implement adequate deepfake labeling, even though both are legally required under the EU AI Act,” Kyle says.
Food businesses do not need to wait for legislation to catch up; they can implement practical defenses immediately.
Food Alert warns that as AI-generated content becomes virtually indistinguishable from genuine evidence, the volume and sophistication of fraudulent complaints are likely to rise. Businesses with robust reporting systems and clear complaint records will be best placed to identify patterns and mitigate risk.
“Prioritize staff training on AI detection indicators. Implementing custom deepfake security awareness training gives employees direct experience with just how convincing AI-generated content has become, while arming them with practical guidance on what to look for,” says Kyle.
“Food businesses should collaborate with food safety and legislative experts to accurately map their vulnerabilities. Specialist consultants and legal teams can help businesses assess their digital exposure, advise on appropriate handling processes, identify operational gaps, and construct documented responses that can assist if a complaint ever reaches an enforcement body or court.”
“Finally, upgrading the complaint logging infrastructure is a critical priority. A structured system that captures the tone, nature, and characteristics of complaints across an entire operation creates vital data visibility.”









