Viral food trends, GLP-1 weight loss drugs, reformulation pressures, and channel fragmentation mean that demand is becoming structurally harder for food and drink businesses to forecast.
Data from our Operations Outlook 2026 research report exposes the limitations of planning infrastructure built for a more predictable consumer market.
Social media drives spikes in demand for ‘aesthetic’ products, as seen with the viral reaction to the M&S strawberry sandwiches, while ‘fibre- and protein-maxxing’ trends are encouraging consumer preferences to change faster than many traditional planning systems can handle.
Our research, based on a survey of over 800 C-suite leaders, shows that many food and drink firms are still struggling to build the data and AI capabilities needed to track and respond to these shifts. The research found that:
- 38% of food and drink leaders cite legacy IT systems as a major challenge to implementing AI, compared with the cross-industry average of 28%
- 35% point to a lack of in-house expertise and skills
- Data also remains an obstacle, with 31% identifying quality, availability, and governance as their top barrier
- Only 28% of food and drink firms also say they have a clear roadmap for integrating AI into their processes, compared with 39% across all industries
Food and drink businesses are now operating in a market where social media can turn a niche product into a national talking point in a matter of hours. Take the example of Lidl launching its own version of Dubai chocolate; when it went on sale at 9:00, it had sold out by 10:24. That’s a major forecasting challenge.
Businesses need the capability to identify emerging signals earlier, understand which trends have ‘staying power’, and translate that insight into faster commercial and supply chain decisions.
Social media is only one source of volatility; food and drink businesses are also contending with sustained pressure on household budgets, which is driving switches between branded and own-label products.
At the same time, advertising restrictions for foods high in fat, salt, or sugar are accelerating reformulation efforts, while growth across direct-to-consumer, convenience, foodservice, and online channels is making purchasing behaviour more fragmented.
The increased use of GLP-1 weight-loss drugs is adding another layer of complexity by changing the types and quantities of food consumers buy, as well as how frequently they shop.
Businesses that combine stronger data governance, AI-enabled demand sensing, and more agile planning processes will be better placed to respond to fast-moving trends and maintain service levels.
These days F&B firms are never tackling just one disruption at a time, these days. It’s several sources of volatility overlapping and feeding one another. A viral trend can collide with a change in health behaviour, a reformulation programme or a shift towards own-label products. That can quickly leave businesses with too much of the wrong stock, too little of the right stock, and margin tied up in waste.
AI can help firms optimise inventory and react more quickly, but it is not a shortcut around poor foundations. Without reliable data and a clear implementation roadmap, businesses risk producing faster answers from incomplete or inaccurate information. It’s about spotting change sooner and adapting operations before competitors do. For firms still postponing investment in their data and planning capabilities, the clock is ticking.
Authors: James Watson and Judith Richardson
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