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Mars turns AI into an ingredient discovery engine – and the rules of food innovation may be changing

Mars says artificial intelligence is moving beyond “writing emails” and into the lab – helping its teams identify new plant-based bioactives, fermentation-driven compounds and lower-impact proteins for future product formulation. The opportunity is real. So are the governance, safety and transparency questions that follow.

AI in food has been easy to dismiss as marketing gloss: chatbots, trend dashboards, automated copywriting. Mars is arguing for something more consequential – using AI to accelerate ingredient discovery itself, and to reshape how new formulations are found, tested and commercialised.

At the centre of the approach is Mars’ work through its Mars Advanced Research Institute and Global Food Safety Center, where research teams are scanning for plant-derived compounds with health potential, alongside alternative proteins that could reduce environmental impact. Mars’ view is that the biggest prize sits in the “in-between space” – functional ingredients that perform in real products, not just in the lab, and that also help solve persistent barriers in plant-based (including taste challenges such as bitterness).

WHY FERMENTATION IS THE MULTIPLIER
Mars is combining plant chemistry with fermentation to widen the search space. The logic is straightforward: mix plants with microbes and you expand chemical diversity dramatically, producing compounds that may not exist naturally in the original ingredients. In practice, that creates a pipeline for novel flavours, functional compounds and potentially new building blocks for reformulation – but also a pipeline of “new-to-market” substances that may trigger regulatory scrutiny and demand robust toxicology and safety validation.

THE ENGINE ROOM: KNOWLEDGE GRAPHS, NOT CHATBOTS
Mars’ ingredient discovery work is supported by LEAP, an AI platform from UC Davis spin-out PIPA. The distinction matters: this is not positioned as a general-purpose large language model trained on the open internet. Mars describes a structured “knowledge graph” approach that links ingredients, compounds, microbes and health outcomes by combining published science, databases and omics data with Mars’ own proprietary insights.

The goal is not to replace scientists – it is to raise the odds of running the right experiments. Mars says it has compared “random choices” and “expert choices” against AI-assisted choices, and in some cases the AI-assisted route improves hit rates. That is an important claim, because in R&D the cost is not just time; it is also the opportunity cost of what never gets tested.

THE GOVERNANCE GAP: SPEED WITHOUT TRUST IS A DEAD END
Mars is also explicit about emerging risks. One concern is “AI learning from AI-generated content” and amplifying errors. Mars says it is building filters to identify AI-generated or low-confidence material and maintains “human-in-the-loop” accountability, including toxicologist sign-off for safety-related decisions.

This is the crux for the wider UK food industry: ingredient discovery can now move at “computational speed”, but consumer trust, regulatory acceptance, and scientific reproducibility still move at human speed. If AI is to become a genuine ingredient pipeline, it must be auditable, explainable enough for safety assessment, and disciplined about what data is trusted.

WHAT HAPPENS NEXT – AND WHY UK EXECUTIVES SHOULD CARE
Mars indicates that ingredient discoveries have already been made, but that bringing new ingredients into products takes time. It expects public progress to be shared within the next six months.

For UK manufacturers, suppliers and investors, the bigger signal is strategic: AI is becoming a competitive moat in formulation and ingredient IP. That will influence:
• Supplier strategy (who controls fermentation capacity and novel ingredient scale-up)
• Claims strategy (what can be substantiated, and what will be challenged)
• Regulatory pathways (novel foods, safety dossiers, and transparency obligations)
• Portfolio decisions (where “plant-based” moves from category to capability)

THE UK FOOD INDUSTRY COUNCIL VIEW
AI-driven discovery will not “solve” nutrition, sustainability or reformulation on its own. But it is clearly changing the economics of experimentation. The winners will be organisations that treat AI as a governed scientific capability – not a hype layer – and that can prove safety, efficacy and consumer value at the pace of scrutiny, not just the pace of computation.

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