Adapt or Fall Behind: The Agentic Imperative for Food Companies

Most organizations recognize that artificial intelligence (AI) holds enormous promise, but many are still struggling to turn that potential into meaningful business results, according to Alon Chen, CEO and cofounder of Tastewise, an AI-powered consumer intelligence and market insights platform.

Speaking during a keynote presentation at IFT FIRST Annual Event and Expo, Chen said the rapid emergence of agentic AI is creating both opportunities and urgency for food and beverage companies. His company’s platform is used by 80% of the world's largest food and beverage conglomerates, he said, helping them apply agentic solutions to everyday workflows.

“People wake up, and they're feeling behind,” Chen said. “They don't know how to make best use of the resources out there, or maybe that a competitor is going to come and grab their market share.”

Many organizations understand that AI holds great promise but don’t know how to tap into it, Chen said, while estimating that about one-third of consumers worldwide use generative AI to research products, which means brands are busily investing in making sure search engine AI summaries represent them well.

“Agentic e-commerce is already making an impact on your brands today,” he said. “If you are using agents, you can actually talk to other agents. But if you're not, you will be left behind. … Every big change requires moving people around, redefining roles and responsibilities. Agentic transformation is a place where just giving people more technology is not going to make the meaningful uplift in productivity and business returns that you're expecting.”

While some organizations continue to map out multiyear digital transformation plans, Chen encouraged companies to pursue shorter, more focused initiatives tied directly to business challenges.

“If anyone is putting forward a three-year plan, please try to challenge them on, ‘What are the impacts and the gains we can be making today?’” he said. “If you are able to understand how consumers are responding and respond in real time, you can actually make sure that your product offering, your packaging, your sizing, or your next menu item is actually tailored and delivered.”

Agentic intelligence can help solve two kinds of challenges, Chen said. On the science side, AI can explore claims like, “Can I get a faster formulation?” or “Can I reformulate my products and brands?”

As for consumer demand, Chen said, the key questions include, “What is the need occasion I need to be creating my product for? What is the belief I need to be addressing? And which audience can I be designing my next products for?”

The ecosystem of agents a company puts into motion needs to account for the “complex funnel” of distribution lines, sourcing, production lines, marketing, demand creation, commercialization, and shelf space, as any experienced, talented product developer would, Chen said.

For R&D teams, this can mean gaining faster access to consumer insights that might previously have taken months to circulate through the organization, Chen observed. “What happens is a system of intelligence … that basically allows your agents and allows your teams to get answers for very, very basic questions: What are moms in Chicago having for breakfast recently? What are the rising diets for Gen Z or Generation Alpha?”

When companies successfully connect consumer intelligence with innovation efforts, the impact can be dramatic. Chen said product development timelines that commonly extended from six to nine months a decade ago can, in some cases, shrink to as little as four weeks.

“It's not about another software subscription,” he said. “It's not about another data source. It's about rethinking how teams are working.”

Trust in AI platforms is essential, Chen said, noting that to build trust, users must be confident in the system’s accuracy. “Every single customer we're signing a deal with has a data analysis and review,” he said. “They have a privacy review. They have a generative AI committee review: How trustworthy is it?”

Chen stressed that in an increasingly AI-driven workplace, curiosity will remain a high-value skill. “There is nothing we cannot solve,” he said. “The question is, what kinds of things are worth solving? Your curiosity is what's going to lead you to the opportunity.”

A decade from now, Chen predicted that marketing teams “will be 100% agentic,” while operational areas such as supply chain, manufacturing, and food science may evolve more gradually. “I think those that are going to adapt are going to be skyrocketing,” he said, predicting that growth will stall for those that fail to do so.

Introducing the keynote session, Jay Gilbert, director of IFT’s AI-powered R&D platform CoDeveloper, framed agentic AI not simply as a technology for improving efficiency, but as a tool for amplifying human potential.

“Imagine having an intelligent partner that helps connect ideas you hadn't considered, one that helps surface relevant research from across disciplines, one that remembers what you've learned over years of experience,” Gilbert said.

Such systems, he said, can help preserve institutional knowledge and free scientists, product developers, researchers, and students to spend more time on distinctly human pursuits.

Using agentic AI effectively “allows every scientist, every product developer, every researcher, every student to spend more time doing what humans do best: being curious, being creative, being collaborative, asking better questions, innovating, and being inspired,” Gilbert said.

The theme echoed Chen's concluding message: While agentic AI may transform how work gets done, human curiosity will remain the force that determines what innovations come next.

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