The summer of 2024 was a wake-up call for the ice cream industry. In France, Nestlé Extreme ice cream had to be recalled due to a cold chain break during transport, raising serious concerns about product safety and quality. The incident highlighted the critical challenge of maintaining the perfect temperature for perishable goods throughout their journey.
Now, AI is stepping in to ensure your favorite ice cream stays frozen from factory to freezer.
The cold chain is the backbone of ice cream logistics, requiring seamless temperature monitoring from production to storage and delivery. Hindustan Unilever Limited (HUL), a key player in the ice cream market, has embraced AI to optimise this process.
In an exclusive conversation with AIM, Satyashali Kawde, assistant CQA (certified quality auditor), HUL, Mumbai, highlighted the company’s adoption of the real-time monitoring system (RTMS). This AI-powered tool ensures optimal temperatures during transportation and storage in India.
“Ice cream is a perishable and highly sensitive product. Maintaining its quality requires meticulous temperature control throughout the supply chain. Last year, HUL introduced RTMS, which uses sensors in dedicated ice cream trucks and storage depots to monitor and adjust temperatures in real time,” he said.
“The tool enables centralised monitoring, live tracking of trucks, and instant alerts on temperature fluctuations,” Kawde added.
This AI-driven system has significantly reduced product loss due to temperature variations, improving efficiency beyond traditional physical monitoring methods.
Forecasting Demand with AI
For Elif Cakir, Unilever’s ice cream supply chain long-term planning lead, weather is more than just a casual conversation starter, it’s an important factor influencing business operations.
In a company blog post, Cakir explained, “Our supply chain spans 60 countries and 35 factory production lines. Ice cream demand is highly seasonal and directly influenced by weather conditions. A single-degree rise in temperature can dramatically impact sales.”
To enhance production forecasting, Unilever embraces AI to analyse weather patterns. In Sweden, AI-powered demand predictions have improved accuracy by 10%, enabling production lines to adjust dynamically. This results in reduced waste, optimised costs, and a supply chain that efficiently meets consumer demand.
“AI helps us determine where and how much ice cream to sell, down to the specific freezer cabinet. It allows us to optimise order placement and delivery, ensuring availability while minimising excess inventory,” Cakir added.
Adapting to Weather Conditions
Unilever uses AI-driven predictive models to fine-tune ice cream production in response to seasonal fluctuations. AI-enabled inventory systems can quickly identify stock locations and reroute shipments to meet the surge in demand if an unexpected heatwave strikes a key market.
Beyond inventory management, AI also contributes to sustainability efforts by optimising delivery routes for refrigerated fleets, reducing energy consumption while maintaining efficiency.
Minimising Waste and Cutting Costs
AI’s impact extends beyond logistics to the manufacturing process itself. By analysing real-time data, AI helps Unilever’s factories adjust production variables, reducing waste and cutting raw material usage, such as vanilla and cocoa, by up to 10%.
Additionally, AI-powered image capture is redefining inventory tracking. With over 1,00,000 AI-enabled freezer cabinets worldwide, Unilever gains live insights into stock levels, preventing both shortages and overproduction.
“This technology eliminates the need for static forecasting models because we now have live data on stock availability. In Turkey, the US, and Denmark, AI-enabled freezers have boosted sales by 8%, 12%, and 30%, respectively,” Cakir shared.
AI and Ice Cream
AI isn’t just making ice cream logistics smarter, it’s helping in marketing and product development, too.
In India, Havmor Ice Cream has partnered with Gan.AI to create personalised advertising campaigns targeting distributors and retailers. By generating over 20,000 customised video ads featuring a popular cricketer, Havmor strengthened its distribution network and boosted sales through tailored marketing efforts.
Meanwhile, a Russian ice cream manufacturer, Chistaya Liniya, uses AI-powered shelf image recognition technology developed by Inspector Cloud. The system audits coolers and analyses product placement, resulting in reduced manual labor and improved data processing accuracy, which in turn enhances sales strategies.
Even ice cream flavours are getting an AI makeover. A Swedish ice cream brand, GB Glace employs AI in flavour development by analysing consumer preferences and flavour trends. AI-powered sensory analysis platforms facilitate rapid prototyping and refinement of new flavours, accelerating product development and enabling the introduction of innovative ice cream varieties.
