By Alon Chen, CEO and co-founder of Tastewise
Key takeaways:
- Food & beverage is complex and fragmented, making it difficult for human teams to spot emerging trends promptly. This creates a particularly strong use case for agentic AI.
- While F&B brands see the technology’s potential, 75% of consumer packaged goods companies are stuck in the pilot stage, with only 18% having successfully scaled AI to real impact.
- Rather than relying on historical data, such as quarterly reports, sales figures, and point-in-time surveys, AI agent deployments require live demand signals to deliver real value impacts to business bottom lines.
An obscure dish on an independent restaurant menu might be the catalyst for the next billion-dollar idea on supermarket shelves.
In an industry as complex and fragmented as food and beverage, however, those signals can be difficult to spot. Consumer demand is constantly being reshaped by seasons, social media, culture, entertainment, economics, health priorities, and the emergence of new flavors, formats, and ingredients. And a trend that emerges in the retail space can quickly ripple across categories, impacting everything from home cooking to K-12 menus.
While market research and data analysis have long helped brands spot market changes, time has always been a limiting factor. Gathering information, analyzing data, and developing concepts takes months, leaving brands at risk of acting on trends that have already played out.
This makes F&B a prime environment for agentic artificial intelligence, advanced AI systems that don’t surface an answer and stop, but run the whole workflow end to end, from live consumer signal to validated concept to the sell-in story that puts it on shelf. Capable of processing information at far greater speeds and volumes than humans, these agents can identify the next best-selling flavor, the packaging that will grab attention, the sales strategy that will land it on shelves, and the marketing campaign that will sell it in a matter of days.
The growing appetite for agentic assistance
AI is already transforming the way consumers discover new products. Historically, F&B brands have competed for attention through advertising campaigns, sampling and tastings, in-store promotions and displays, and paid placements on supermarket shelves.
More recently, social media has become a leading source of product discovery and social proof among consumers.
As we enter the agentic age, consumers are increasingly turning to AI to help them decide what to eat, drink, and try next. According to Similarweb’s 2026 Generative AI Brand Visibility Index, 35% now use AI for product discovery, more than double those who use traditional search engines.
Consumers are particularly trusting of AI when it comes to F&B choices. Recent Accenture research found 80% of snack and beverage consumers were open to collaborating with an AI agent to find options that match their diet, budget, and taste preferences.
Instead of browsing menus and feeds seeking inspiration, consumers are simply asking AI, “Which new flavors will I love?” or “What product should I try next?”. Which brands are recommended by AI assistants (and which are not) is a white space that most CPGs have yet to consider seriously.
From pilot stage to the production line
The industry is by no means an AI laggard. Most consumer packaged goods (CPG) companies recognize agentic AI’s potential and are actively trying to make it work, with F&B brands among the manufacturing industry’s biggest AI investors.
However, they have largely struggled to turn those experiments into deployments that deliver real business value. According to a recent report from BCG and The Consumer Goods Forum, 75% of CPG companies are stuck in the pilot stage, and 82% have struggled to scale AI to unlock real impact. Most commonly, they cite pilot economics not translating into full-scale business results as the main barrier. However, this bottleneck is no indication that AI cannot live up to expectations, given that 18% have succeeded.
The problem is data. The issue is not a lack of data; most teams have more data from more sources than they know what to do with it. You can build a team of the brightest human talent, but it will struggle to deliver results if they aren’t given the right tools to succeed. The same applies to an AI agent. It can process information and complete tasks at a far superior speed. With the pace of change of today’s consumer, the brands that have the right tools to evaluate that data and create the right business outputs from it are the ones that are building competitive advantage.
Data quality is also a crucial element; quarterly reports, historic sales data, and limited surveys fielded weeks or months earlier will prevent even the most sophisticated agents from providing value. These sources provide a picture of trends that have already materialized, which isn’t useful in a market that is constantly undergoing change.
The missing ingredient: live demand signals
To be among the 18% seeing ROI on their agentic investments, F&B brands need to invest in agents with access to live demand signals as their context layer: what ingredients are restaurants adding to their menus most frequently? Which dishes are consumers actively seeking out? Which products are flying off supermarket shelves?
In other words, what are people ordering, cooking, and eating now – and why? These signals give brands an early indication of where demand is heading, and how they can capture the moment.
According to Tastewise data, Tonkotsu ramen now appears in two-thirds of restaurant occasions where Gen Z orders soup, and demand for beef tallow has quadrupled, coinciding with a 33% decline in demand for plant-based meals among the young generation. Likewise, anti-nausea is now a top eating priority for over 20% of GLP-1 users, influencing food choices among a growing number of consumers turning to the weight loss medication.
Human teams can uncover and act on these patterns, but those processes take time. That’s where AI investment can deliver genuine commercial value: helping brands expand distribution, accelerate innovation, and drive demand; identifying opportunities before niches become saturated; and avoiding the cost of developing products for markets that have already moved on.
However, the combination of ingredients can make or break a dish. For brands struggling to see results from their agentic AI pilots, the answer likely lies in the data their agents are fed. The perfect recipe requires agents that can process information at speed, and automate the marketing campaigns, product ideas, and sales strategies to act on it, driven by live, constantly updated data signals that pinpoint precisely how consumer appetites are evolving.
Alon Chen is the CEO and co-founder of Tastewise, the agentic intelligence system for food and beverage. Previously Chief Marketing Officer for Google in Israel and Greece, Chen has grown Tastewise into the go-to agentic intelligence system for F&B brands, including PepsiCo, Nestlé, Kraft Heinz, Campbell’s, and Givaudan. Trained on Tastewise’s extensive real-time market trackers, continuously updated consumer panels, and over 300,000 hours of expert oversight, its AI agents support the entire F&B workflow – from R&D to marketing and sales – turning industry-leading market intelligence into production-ready concepts in weeks.
