Artificial intelligence is beginning to influence how some American consumers discover food, and Conagra Brands sees the change as particularly relevant to the rapidly evolving snack market. The company’s research found growing interest in higher-protein foods, bold flavours and products associated with specific health goals. Its analysis covered more than 53 million shopping transactions involving 17,000 snack products, combined with other consumer behaviour data.

The important development is not simply that consumers are asking artificial intelligence for food recommendations. It is that AI allows shoppers to describe a need rather than search for a particular brand. A consumer can ask for a high-protein snack, a product suitable for a particular diet or something matching a specific health objective. That changes the way products compete for attention. For food manufacturers, the shift could make product attributes increasingly important relative to traditional brand discovery.

AI Changes the Starting Point of the Shopping Journey

Traditional online shopping usually begins with a product or category. A consumer might search for chips, protein bars or meat snacks and then compare brands. AI-assisted shopping can begin with a problem instead. A shopper can describe what they want in ordinary language and receive a selection based on nutritional content, ingredients, price or personal preferences. That means the consumer does not necessarily need to know which brands offer the relevant product before beginning the search.

The change could be significant in a snack market where the number of choices is enormous. Conagra’s analysis identified thousands of products across the category, making discovery increasingly difficult through conventional browsing alone. Artificial intelligence can potentially reduce that complexity by turning a large catalogue into a smaller list of products that appear relevant to an individual’s request.

Conagra’s findings indicate that consumers are increasingly looking for snacks with a specific purpose, including protein, energy and other health-related benefits. The growth of weight-loss medicines has also contributed to greater attention to protein and nutritional composition as consumers reconsider what they eat and how frequently they eat. This creates an opportunity for food manufacturers because products can increasingly be marketed around functional attributes rather than only taste.

Protein content is one example. A consumer seeking a convenient source of protein may be less interested in a traditional brand message and more interested in whether the product meets a particular nutritional requirement.AI can make that distinction more visible because it can compare products according to attributes that would otherwise require shoppers to inspect multiple labels.

The result is a potential shift from brand-led discovery to need-led discovery.

Younger Consumers May Accelerate the Change

Younger consumers are particularly accustomed to using digital platforms to discover products, compare information and receive personalised recommendations. That does not mean all younger consumers will use AI for food decisions, but the technology fits naturally into existing habits built around algorithmic recommendations.

The wider food industry already relies heavily on digital data to understand consumer behaviour. Search activity, social media trends, retail transactions and online reviews provide information about changing preferences. AI adds another layer by allowing consumers themselves to articulate their preferences directly. This creates a feedback loop. Consumers tell AI systems what they want, AI systems recommend products, and manufacturers study those patterns to develop new products. Over time, product development could become more closely connected to highly specific consumer requests.

The implications extend beyond advertising. If manufacturers can identify increasingly precise consumer preferences, they can develop products designed for narrower segments.

Instead of launching a generic snack aimed at the largest possible audience, a company could create products around specific nutritional or lifestyle needs. That could include higher-protein products, snacks with particular ingredients or products designed around specific eating occasions.

Conagra’s research found that ingredient quality is becoming an increasingly important differentiator, while products using ingredients perceived as simpler or less processed are gaining attention. The company’s data also identified strong growth in some specialised categories. AI could accelerate this segmentation because consumers can describe very specific requirements without knowing which existing products satisfy them.

However, there is also a limitation. AI recommendations depend on the quality of available product information. If nutritional data, ingredient lists or product descriptions are incomplete, recommendations can become less reliable.

Brands Must Compete for AI Recommendations

The emergence of AI-assisted shopping could eventually create a new form of competition between food manufacturers. Companies have traditionally competed for supermarket shelf space, search rankings and advertising visibility. They may increasingly need to ensure that their products are accurately represented in digital recommendation systems.

That could make product data an important commercial asset. Accurate nutritional information, ingredient details, pricing and availability will become more important if consumers increasingly rely on AI to compare products. There is also a question about how recommendation systems determine which products to present. Consumers may assume that AI recommendations are neutral, while manufacturers may seek ways to influence their visibility. This makes transparency increasingly important as AI becomes part of purchasing decisions.

For Conagra, the shift offers both opportunity and risk. Products that match emerging preferences can gain visibility, but consumer demands can also change quickly.

The Snack Industry Is Moving Toward Personalisation

Artificial intelligence is not replacing taste, habit or brand loyalty. Instead, it is adding a new layer to how consumers discover products. The significance for snack manufacturers lies in the possibility that consumers will increasingly start with personal requirements and let technology identify suitable products.

That could favour companies capable of rapidly adapting their product portfolios and communicating detailed product information. The snack market is already large and growing faster than the broader food market, making even relatively small changes in consumer behaviour commercially significant.

The emerging model is therefore less about AI choosing food for consumers and more about AI changing the path through which consumers find food. The brands that succeed in that environment may be those that understand both traditional consumer preferences and the increasingly specific questions shoppers ask when deciding what to buy.

(Adapted from Reuters.com)

Categories: Economy & Finance, Strategy