“Listening to the market before it speaks – How a supermarket chain used AI to redefine demand”
Problem
Demand forecasting in food retail with market intelligence and agentic AI
A leading national food retailer was facing a familiar but increasingly existential problem: unpredictable fluctuations in demand for fresh produce, seasonal items, and regional product ranges. At the same time, pressure from discounters and delivery services was mounting. Traditional demand forecasts were based on averages, weekly schedules, and gut feelings—too sluggish for today's markets.
The Decision: The company decided to take a disruptive step: combining AI-supported demand forecasting, market intelligence from external sources (social media, news, trends), and Agentic AI—autonomous AI systems that can learn, decide, and react in real time.
Solution
An agent-based AI system was introduced that not only analyzed sales data but also processed external market impulses: e.g., trend analyses on food preferences, social media sentiment on brands, regional events, and even health warnings. Agentic AI automatically monitored all relevant data sources, independently trained its models, and generated not only forecasts but also concrete recommendations for action regarding quantity planning, price control, and availability.
Benefit
The result:
- 39% more accurate demand forecasts for fresh produce
- 24% less write-offs (loss of goods)
- 17% increase in sales through targeted campaign planning
- 80% of planning decisions were AI-initiated
Particularly noteworthy: On Saturday morning, Agentic AI automatically suggested reducing the order quantity for a regional product based on a negative trend in local social media data. The decision prevented overstocking in more than 70 stores.
The learning: Market intelligence provides context. Agentic AI provides action. Together, they create a system that not only predicts, but also thinks for itself. In a market that reinvents itself every day, you don't need static dashboards—you need learning, decision-making systems. The difference between reacting and acting? Today, it's called Agentic Intelligence.
Quote from the project: “We used to measure demand. Today, we understand it—before it arises.” – Head of Data Strategy, Food Retail