AI emerges as strategic tool in product development

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AI emerges as strategic tool in product development

29 Sep 2025

Mari Rydings

Mari Rydings is a versatile content creator, editor and marketer with experience developing dynamic, results-driven materials for B2B and B2C audiences. As the editorial director for Avant Food Media, she leads the day-to-day editorial operations for the company’s print and digital magazines, newsletters and social media platforms. Outside of work, she loves reading, hiking, putting together jigsaw puzzles and spending time with her husband and their twin daughters.

KANSAS CITY, MO — AI is no longer the technology of the future … it’s here. It’s also proliferating at breakneck speed and transforming how food and beverage companies do business. Embracing AI in key areas can help organizations optimize operations, boost productivity, increase profits and decrease costs.

As evidence of increasing adoption, Precedence Research predicts the global market size for AI in food and beverages will grow from $15.36 billion in 2025 to approximately $263.80 billion by 2034, a CAGR of 37.30%. In the commercial baking space, nearly 70% of the industry has adopted or plans to adopt AI in some capacity, according to “AI in the Commercial Baking Industry,” a pulse survey from the American Bakers Association (ABA), with respondents indicating marketing and sales, supply chain management and manufacturing as top AI-focused business functions.

“AI is really just taking math and applying it to something that makes the world faster,” said Chad Larson, COO for Springfield, IL-based Mel-O-Cream Donuts during a Baking Industry Forum panel discussion at BEMA Convention 2025. “The theme behind it is always going to be, ‘What do we do, and how do we do it with less?’”

R&D is a key area where AI is thriving, specifically as it relates to new product development (NPD), where staying ahead of trends and speed to market are competitive advantages for baking companies. Regarding R&D, the ABA survey reported that 17% of companies are currently using AI, 11% have either tested or plan to test AI pilot programs, and 24% intend to adopt AI solutions in the next 12 months.

The biggest drivers of AI adoption in NPD are speed to market, actionable insights and consistent product quality. With the right tools, bakeries can generate ideas, explore new ingredients, reduce the trial-and-error process and the risk of failure, and generate consumer-centric innovation.

“AI can find ingredient alternatives, reduce formulation cycles and cut costly bench tests, which speed up the path to market,” said Greg Heartman, VP of product management at TraceGains. “It also allows teams to model new products and reformulations — down to ingredients, packaging and ESG criteria — before anything hits the lab. It enables product developers to explore unlimited ‘what if’ scenarios with precision, while tracking consumer trends, regulatory shifts and supplier risks in real time. From source to shelf, AI is helping food brands move faster and smarter.”

“AI enables product developers to explore unlimited ‘what if’ scenarios ... From source to shelf, it is helping food brands move faster and smarter.” — Greg Heartman | VP of product management | TraceGains

Many companies use semantic AI to track online consumer conversations across social media platforms, blogs, forums and review sites and mine them for consumer behaviors, emerging — or fading — trends, and even language that could be used in marketing campaigns.

As part of its Taste Tomorrow proprietary research program, ingredient company Puratos USA combines digital insights with extensive consumer survey results and sensory research to accelerate product ideation and recipe development and help customers bring new products to market on a truncated timeline.

“We look at long-term, fast-evolving and seasonal trends,” said Benjamin Bado, data and digital innovation manager at Puratos. “We can gather thousands of ideas, filter them down to the most relevant ones and invest in those. AI enables us to move quickly in this kind of exploration. What used to take months can now be done in days; we can create a recipe and gauge market response almost immediately. Of course, adjustments are still needed to meet requirements for value, machinability, processes and taste, but AI accelerates the core stages that typically take the most time.”

Applying predictive modeling during formulation can also reduce some of the trial and error because it can simulate how different ingredient combinations will impact shelf life, food safety and product quality before testing even begins.

“This data-driven approach enables our customers to reduce development time; streamline innovations; and bring clean-label, sustainable solutions to market with greater confidence,” said Ashley Robertson, director of marketing and communications for Corbion. “AI empowers manufacturers to turn complex datasets into clear, actionable direction. This allows brands to innovate more efficiently and stay ahead of evolving consumer expectations.”

This has been adapted from the August | Q3 2025 issue of Commercial Baking. Read the full digital edition here.