Artificial Intelligence (AI) is rapidly reshaping industries worldwide, and the food sector is no exception. From manufacturing operations to supply chains, many food companies have already embraced AI to improve efficiency. Yet, there is one area where the technology is making only limited progress: food safety.
This reluctance to integrate AI into food safety processes is surprising, especially considering that both humans and machines currently tasked with ensuring food safety are far from perfect. AI proponents argue the technology is virtually bulletproof, offering a way to drastically reduce errors.
In 2023, four Cornell University academics—Chenhao Qian, Sarah Ingersoll Murphy, Renato Orsi, and Martin Wiedmann—highlighted the vast potential of AI in food safety in the Annual Review of Food Science and Technology. The possible applications, they wrote, “are broad” and span from “food safety risk prediction and monitoring” to optimising safety throughout the supply chain. Furthermore, AI could help “improve public health systems,” for instance, by providing early warnings of outbreaks and tracing the source of foodborne pathogens.
Supporting this, research from UC Davis shows how AI combined with optical imaging could rapidly and accurately detect bacteria in romaine lettuce, which could be a key tool in preventing foodborne outbreaks. Despite such promising possibilities, AI technologies in food safety still “lag behind in commercial development” compared to areas like agricultural production or marketing, the Cornell researchers pointed out. This slow adoption is primarily due to “obstacles such as limited data sharing and limited collaborative research.”
Finding major food companies openly embracing AI for food safety is challenging. Among those approached, a European group confirmed its work with AI in this area but admitted it was “premature” to comment. Another global player mentioned AI’s use in its supply chain and manufacturing but noted that food safety was not yet a focus.
However, Nestlé has taken significant steps, with a spokesperson explaining: “We’ve developed artificial intelligence tools that use ‘big data’ in real time… to identify and target potential risks in our supply chain.” Chocolate giant Lindt & Sprüngli, meanwhile, remains cautious, stating they are “closely observing the development of AI tools in the area of food safety” but are not ready to share more details.
The slow uptake is not without reason. According to industry experts, the causes are varied. “Some applications are rising, but [they] are still facing massive roadblocks such as change management and connectivity issues in factories,” explained Amine Raji, founder of Spore.Bio, which uses machine learning to identify pathogens. Raji adds that although AI-powered cameras and sensors are being trialled to monitor hygiene practices, such as hand washing and equipment sanitation, this remains an early-stage development.
Consultancy AlixPartners’ Abhinav Agrawal has seen some clients experiment with AI in food safety, but agrees that it is still in its infancy. He points to pilot projects that include AI models designed to predict foodborne illness outbreaks, optimise inspections, and improve traceability.
Raji, who previously worked at Nestlé, notes that AI is more likely to be adopted first in high-value industries like pharma or cosmetics before gaining traction in the food and beverage sector. Suzanne Livingston, Vice President at IBM, also sees promise in how AI can address accountability and compliance within supply chains. She believes this could lead to fewer contamination events, recalls, and compliance failures, benefiting companies by enhancing reputation and sustainability.
Data management is another potential game-changer. Raji pointed out that “quality managers have decisions to make based on thousands of data points,” many of which are still paper-based. AI could revolutionise this, enabling real-time processing and ensuring food products are safe before leaving the factory.
Regulatory bodies are also beginning to explore AI’s potential. In the UK, the Food Standards Agency (FSA) developed a proof-of-concept AI tool aimed at improving food hygiene inspections. Although the tool was not deployed due to “multiple reasons and competing priorities,” its development shows regulators are thinking about AI’s role in food safety. Many believe it’s only a matter of time before such systems are rolled out more widely.
Despite these signs of progress, the adoption of AI for food safety may face significant regulatory hurdles. Agrawal suggests regulatory issues, rather than technological ones, might slow progress. “Fines in the case of machines/AI can be much higher due to the 100% accuracy expectation,” he notes. This discrepancy could cause companies to hesitate when it comes to AI-based safety measures, fearing regulatory penalties that human error might avoid.
The Cornell researchers also identified “multiple factors” hindering AI’s progress in food safety. Chief among these was the perception of risk within businesses, alongside concerns that AI tools could expose them to greater scrutiny. They wrote: “One key reason seems to be the limited availability of data needed to develop and implement AI tools for food safety applications.” Businesses are wary of data privacy issues and the reputational risks of sharing information, they argued.
The challenge of standardising data from different sources and the broader lack of regulatory frameworks also complicates matters. As such, while the benefits of AI are becoming clearer, its full potential in food safety remains untapped for now.
Yet with time, collaboration, and regulatory clarity, AI could transform food safety processes, making them faster, more efficient, and far more accurate. The question is: how long will the food industry take to make the leap?