AI Enhancing R&D For Dairy Processors
HART Insight Summary
Artificial intelligence is becoming a practical tool for dairy product development, helping processors analyze data, evaluate ingredient interactions, and accelerate formulation work. While dairy innovation has traditionally relied on experience and trial-and-error testing, AI is increasingly being used to identify opportunities, improve efficiency, and help bring new products to market faster.
Key Takeaways
- AI can help shorten product development timelines by analyzing large datasets and predicting formulation outcomes.
- Processors are exploring AI to improve ingredient functionality, optimize recipes, and identify emerging consumer preferences.
- AI is increasingly being integrated into R&D workflows, complementing the expertise of food scientists rather than replacing it.
- Strong data management and secure enterprise-level AI tools are critical for successful implementation.
At A Glance
- Estimated Reading Time: ≈4 minutes
- Original Publish Date: May 29, 2026
- Source: Dairy Processing
Artificial intelligence (AI) is steadily moving from the plant floor to the product development lab, opening new possibilities for dairy processors looking to speed innovation, refine formulations and respond faster to changing consumer demands.
While the dairy industry has long relied on the expertise of food scientists and formulators, AI tools are increasingly complementing that knowledge by analyzing large data sets, predicting formulation outcomes and helping R&D teams move from concept to commercialization more efficiently.
For dairy processors facing intense competition and pressure to launch differentiated products, AI-driven formulation tools offer the potential to shorten development cycles, optimize ingredient functionality and reduce costly trial-and-error experimentation. From predicting texture and flavor interactions to identifying new ingredient combinations, artificial intelligence is becoming an important tool in the dairy innovation toolbox.
As these technologies mature, processors are discovering that AI can enhance – not replace – the expertise of experienced dairy scientists, allowing them to focus on creativity and strategic product development while machines handle complex data analysis.
Investment In AI
The use of AI may help product developers predict emerging flavors and textures, while more advanced applications combine knowledge of flavor chemistry, consumer data and machine learning for more detailed and complex results, said Steve Brown, a former executive at Google Deepmind and Intel.
The Institute of Food Technologists (IFT) forecasts that nearly 50% of food and beverage companies plan significant investments in AI and supply chain technologies this coming year. Companies think the technology will enable them to make decisions faster and boost production efficiency to generate savings across the supply chain.
“There’s an 80% failure rate on new (food) products,” Brown said. “What if you can have AI predict whether a formulation was going to be something that consumers would love or not? How can you use that to optimize product development?”
Experts are adamant that AI is here to stay.
“AI is not a trend. It’s the engine for the next generation of food and beverage innovation. Many firms are moving beyond pilot programs and integrating AI into their core business strategies,” said David Soley, founding partner of The AI Strategies Group, Lake Forest, Ill. “Those who take the lead in AI adoption will inspire cultural transformation and position their organizations for long-term market and revenue growth.”
The Right Tools
Early adopters are looking at which AI tools may work for their respective business. They are evaluating where AI improves workflow and where it creates complications.
Selecting the proper AI tool is critical to success. More platforms and models are becoming available, creating confusion for scientists who just want to work in the lab.
“From a due diligence perspective, management must select AI tools they trust,” Soley said. “These tools provide the business with control over the type of information being entered into their AI systems.”
Jim Lombardi, head of strategy, Innov8NXT, said: “Some product developers are using Chat GPT as an end-to-end resource and wondering why the product trials taste sub-par. You can use Chat GPT to look at trends, scan some articles and ‘cook down’ information so you can make a great decision on what is the next big thing.”
Such open AI platforms should not be used in formulation work, Lombardi cautioned. They make companies vulnerable to lawsuits for theft of intellectual property.
“It’s a huge risk,” Lombardi said. “Enterprise-based AI formats, on the other hand, keep information within an organization. They assist with innovation and renovation (reformulating) when you spend the time to create a great foundation of data.
“AI is not a spreadsheet; it works in tandem with good solid data points. The better the foundation, the better the learning and speed of iterations. You should expect to see about a 30% reduction in bench time within six to nine months when using AI assistance.”
Speed To Market
Increased speed in product development is valuable for corporate innovation investments, which have been decreasing over time for many companies, according to McKinsey & Co., New York. Applying AI may improve productivity, propel growth and help solve some of the complex challenges companies face. McKinsey estimates that $360 billion to $560 billion of potential annual economic value could be unlocked by using AI to accelerate research and development.
“AI is already accelerating our food formulation work by enhancing processes, increasing speed to market and improving accuracy,” said Abhishek Roy, senior director for global digital and artificial intelligence, Cargill, Minneapolis. “Our food scientists, for example, use AI in recipe discovery by analyzing ingredient interactions, optimizing formulations and generating recommendations of novel recipes based on target parameters and consumer preferences.
“We’re also using AI-driven research tools to speed knowledge sharing and product development. Our teams use AI to support everything from optimizing fermentation processes to microbiome assessments and ingredient reformulations, helping bring new solutions to market more quickly, using ingredients that meet fast-changing consumer preferences.”
Ashley Robertson, director-global marketing and communications, Corbion, Lenexa, Kan., said: “Essentially, AI is helping researchers spend less time collecting data and more time creating meaningful innovation.
“AI has also become an incredible listening tool. By analyzing social media conversations, reviews and market data, it helps brands pick up on consumer sentiment and emerging trends almost in real time. That gives companies a clearer picture of where demand is shifting and allows them to respond faster with relevant products and messages. It’s a way to stay genuinely in tune with consumers and meet them where they are.”
Food and beverage product developers may rest assured there needs to be a balance between bench-top experimentation and AI-assisted formulation. Product development still needs the human element.
“Some food and beverage formulators have ‘chicken little syndrome,’” Lombardi said. “The sky is not falling. You will not be losing your job. What AI can do is free up time for more true innovation in a more efficient manner.”
He explained that many companies are focusing on reformulating products to meet evolving consumer trends and regulatory changes. Reformulations take a lot of time that could be spent doing more proactive product development rather than reactive reformulating.
“We’re using AI as an engine for innovation,” Roy said. “This engine expands the speed and scope of what’s possible but always relies on our experts for final analysis and application.”
Robertson added: “AI is at its best when it’s used to amplify human thinking, not replace it. The technology can process massive amounts of information and surface possibilities, but people still bring the critical context, the scientific understanding, creativity and intuition that turns data into insight.”
Mike Leonard, chief innovation officer and head of protein fortification for Ingredion Inc., Westchester, Ill., said underpinning the company’s AI efforts is years of proprietary data that links chemistry, structure and consumer insights. The combination enables the company to identify unmet consumer needs in the market, and translate them into technical specifications and ingredient performance targets.
“The faster we can go through all these stages and with higher probability of success, the more success we’re going to have in the marketplace, the more success our customers are going to have, the stickier innovation is going to be for them and the more benefits we can deliver,” Leonard said during the company’s investor day this past fall.
There are several AI platforms to explore in food and beverage formulating. Some function as innovation and business development platforms, by collecting internal and external knowledge.
“Such a platform guides and supports ingredient concept development and streamlines the product-to-market development process,” Soley said. “It enables users to generate, design and build new ingredient solutions while also defining service offerings for product development and customer engagement. It connects organizations across the value chain and helps manage ingredient innovation using data-backed decision making.”
FoodChain ID, Fairfield, Iowa, offers a platform that analyzes current formulations and applies guidance, providing real-time insights and warnings that accelerate time to market. The process may reduce costly maintenance and rework by innovation teams, according to the company. It has been described as akin to having senior staff continually available to support and guide the team throughout the development process, said Wes Frierson, vice president of enterprise solutions at FoodChain ID.
Robertson explained how AI can assist in scale-up and manufacturing.
“AI is taking on some of the industry’s most persistent challenges – efficiency, quality and consistency,” she said. “Companies are using it to predict maintenance needs before breakdowns happen, optimize supply chains and model how different production variables affect product outcomes. By simulating those scenarios digitally, teams can make smarter decisions and move from concept to production with fewer risks and delays. It’s making innovation faster, safer and more data-driven.”
HART Perspective
As dairy processors look for ways to innovate more efficiently, AI may help bridge the gap between product concepts and commercial production. Faster formulation cycles can create opportunities to respond more quickly to market trends, but successful commercialization still depends on consistent processing, scalable production systems, and reliable operational performance. AI may accelerate decision-making, but execution remains critical.
What This Means For Dairy & Cheese Plants
Product Development: Faster formulation and testing cycles may reduce time-to-market for new products.
Scale-Up: New formulations must still transition successfully from the lab to commercial production.
Data Quality: Reliable production and ingredient data become increasingly valuable as AI tools evolve.
Operational Consistency: Efficient, repeatable processes help support innovation while maintaining product quality and throughput.
Attribution
This summary is based on industry reporting originally published by Dairy Processing. HART Design & Manufacturing has added independent analysis and dairy-processing context. The original publishers did not contribute to or review these additions.
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