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With the 2025-2030 US Dietary Guidelines set to reshape the market, food companies face an implementation emergency. Beyond R&D, organisations must rethink structures and processes, using AI to adapt, anticipate change, and build future-ready portfolios. Alisia Heath, VP of R&D at NotCo, explains how F&B innovators can harness AI to navigate the new policy landscape.
The newly introduced US Dietary Guidelines signal a major shift in how Americans are encouraged to eat, with a renewed mandate to prioritise 'real food,' reduce sugar, sodium and saturated fats, and move away from highly processed formulations. While nutrition policy can change overnight, traditional product innovation timelines still move at a glacial pace. For legacy R&D teams, adapting portfolios to meet evolving expectations typically takes 18 to 24 months, often requiring millions of dollars in reformulation efforts.
Regardless of where brands land on the new food pyramid itself, the broader takeaway is clear: the rules are shifting. The existential question now facing the industry is how to pivot an entire portfolio toward 2026 standards when most innovation cycles remain analogue.
A new era, with unanswered questions
At a high level, the updated guidelines reinforce themes the industry has been navigating for years: improving nutritional profiles and delivering functional benefits like fibre and protein. However, ambiguity remains. While the guidance encourages consumers to avoid 'highly processed' foods, it stops short of offering a clear, operational definition.
For food companies, this creates a complex decision-making environment. To future-proof their pipelines, brands will need to make informed assumptions and accept the risks associated with reformulation now to stay ahead of the curve. It is clear that clean label expectations aren’t going anywhere; therefore, the closer companies can get to whole ingredients, the more risk they mitigate as policies change.
Why traditional R&D timelines no longer work
Moving toward fewer processed ingredients is far from straightforward. Many legacy products rely on functional ingredients designed for stability, shelf life and cost efficiency. Removing or replacing these components ripples across the entire product equation.
Changes in processing can impact:
Flavour and texture consumers already love
Shelf life and food safety
Cost of goods and price accessibility
Supply chain resilience
Each product is a multidimensional system: taste, cost, regulation, nutrition, sustainability and shelf life all interact. Adjusting one variable affects every other outcome. Current linear R&D methods make reformulating this complexity too expensive and slow, limiting the number of iterations companies can realistically attempt. To address this, companies need to rethink their entire workflows, not just speed up individual steps.
Rethinking innovation as a data challenge
One of the most important shifts underway in food R&D is the recognition that innovation is no longer just a lab problem; it’s a data problem.
Through Giuseppe AI, our proprietary platform, NotCo is collapsing the traditional time-to-market from years into weeks. Giuseppe synthesises ingredient chemistry, sensory readouts, manufacturing parameters and consumer data into a single decision-making engine.
This allows us to:
Reduce trial and error: We reduce physical trial and error by up to 10x, transforming bold ideas into market-ready products with unprecedented speed.
Solve multidimensional challenges: The platform processes thousands of variables simultaneously. For example, in a recent beverage project, Giuseppe was able to 100% match the quantitative sensory experience of the full-sugar product, reducing the total sugar content from over 10g by 80%+ in just five weeks.
Bridge the policy-to-shelf gap: AI becomes the missing layer between nutrition guidance and the shelf, helping brands pressure-test formulations against new frameworks instantly.
The next wave of innovation in action
We are already seeing this transformation in action through our work with major CPG partners. Through our partnership with Barry Callebaut, we are merging 100 years of chocolate expertise with AI to unlock health-forward formulations. Similarly, with The Magnum Ice Cream Company, we are piloting AI to solve complex formulation challenges in record time, ensuring they continue to shape the category while meeting evolving dietary expectations.
In another recent case driven by HFSS (High in Fat, Salt or Sugar) regulations, we developed a sugar-free chocolate that achieved 100% less added sugar and 60% less sodium while securing a critical HFSS score of 3. By mapping the sucrose time-intensity curve via Giuseppe, we achieved a full-flavour profile in just three trials, preventing significant revenue loss for the client.
As policy pressure and consumer demand continue to intersect, innovation is likely to accelerate most rapidly in categories where health perception and convenience overlap, including ready-to-eat meals, snacks, beverages, and better-for-you indulgences.
Leading with curiosity
For R&D leaders beginning to explore these tools, the most important mindset is curiosity. Artificial intelligence is not replacing scientific expertise; it is amplifying it.
AI adoption is not a one-time upgrade; it is an ongoing capability-building process that will define how quickly companies can adapt to future shifts. As the 2025-2030 Dietary Guidelines make clear, the pace of change in food is only accelerating.
The organisations that will thrive are those willing to rethink workflows, encourage experimentation and equip their innovation systems to evolve as fast as the policy does.
