The Role of AI in Food & Beverage Formulation: Opportunities and Challenges
Artificial Intelligence (AI) is transforming industries across the board, and the food and beverage sector is no exception. One of the most exciting areas of development is AI-driven formulation, where machine learning models assist in creating nutritional and bakery blends. However, while AI offers powerful advantages, it also comes with risks and limitations that companies must carefully navigate.
The Risks of AI in Formulation
Scott Jensen, VP of R&D at Repco, highlights a key concern: AI is only as reliable as the data it is trained on. While AI can process vast amounts of information quickly, it may pull from outdated or even incorrect sources.
“One of the challenges I’ve seen with AI is that it can make things up,” Jensen explains. “It normally comes back with a response, but it assumes that it’s right—and it may not be.”
This raises critical issues for formulation, where accuracy is paramount. Factors such as cost, solubility, bioavailability, and regulatory compliance all play a role in developing a blend. AI might be able to analyze some of this information, but it struggles with nuances like ingredient sourcing, organic certifications, and dietary restrictions. Without human oversight, AI could suggest formulations that don’t align with regulatory standards or consumer expectations.
AI in Ideation: A Starting Point, Not a Solution
Despite its limitations, AI is proving valuable in idea generation and early-stage formulation. AI can help companies develop an initial framework for new formulations, similar to how a product developer might analyze existing items on store shelves for inspiration.
“If I’m looking for, say, a men’s multivitamin formula, I could ask AI what a balanced blend might look like,” Jensen says. “But from there, I’m going to fact-check things and ensure it makes sense for what I’m looking for.”
This suggests that AI is best used as a brainstorming tool rather than a decision-maker. By combining AI’s computational power with human expertise, companies can speed up the development process while ensuring accuracy and innovation.
Limitations in AI for Nutritional Blends
AI’s ability to recognize trends and patterns is impressive, but it falls short when deep industry knowledge and experience are required. Some key limitations include:
- Regulatory Uncertainty – AI may suggest ingredients that are not legally permitted in specific markets.
- Supply Chain Challenges – AI does not always account for ingredient availability, lead times, or ethical sourcing.
- Human Expertise in Quality Control – Certain aspects of food formulation, like texture and sensory attributes, still require human judgment.
Repco addresses these challenges by maintaining a structured question-based approach to formulation. By asking the right questions at the right time, their team ensures they avoid wasted time, dead ends, and compliance issues.
How AI is Used in Today’s Formulation Processes
While AI is not replacing human experts, it is increasingly being used as a research assistant. According to Jensen, he treats AI much like a web search tool, using it to gather initial insights before refining results manually.
For example, if a company requests a multivitamin formulation, AI can generate a preliminary list of ingredients. From there, human experts can:
- Adjust the formula for cost efficiency
- Remove ingredients that don’t align with customer requirements (e.g., non-GMO or vegan)
- Optimize the blend based on bioavailability and market trends
Will AI Replace Human Expertise in Formulation?
Jensen and industry leaders agree that while AI is becoming smarter, it cannot replace human intuition, experience, and creativity. Some aspects of formulation, such as baking performance and texture, still require a hands-on approach.
“Even today, we don’t have good tools to take the place of a baker’s hands or a flour miller’s expertise,” Jensen notes. “In the future, AI might help fill some of these gaps, but we’re not there yet.”
The Future of AI in Formulation
As AI technology evolves, companies are investing in ways to enhance its capabilities. Some firms are exploring AI-driven market implementation tools, which could accelerate product development and improve supply chain forecasting. However, these innovations are still in their early stages.
“The biggest challenge I see is that these are early-stage technologies,” Jensen explains. “How far they get, and what limitations they overcome, will depend on ongoing developments in the industry.”
Over the next one to three years, AI will likely play an increasingly important role in food and beverage formulation. However, human expertise will remain essential for making final decisions and ensuring product quality.
Conclusion
AI is revolutionizing formulation by making research faster and more efficient, but it is not a standalone solution. The most successful companies will be those that integrate AI with human expertise, using it as a tool for innovation rather than a replacement for experience.
As the industry moves forward, AI will continue to complement traditional formulation practices, helping food and beverage companies stay ahead of trends while ensuring quality, safety, and compliance.
