Retail is no stranger to automation. From self-checkouts to personalised offers, the industry has already adopted technology to make shopping faster, smoother and more convenient. Today, the spotlight is firmly on AI-powered chatbots, virtual assistants and robots promising to transform the customer experience. For example, Just Eat recently launched an AI voice assistant that helps customers decide what to eat with ease.
Yet some of the most valuable applications of AI in retail are actually happening behind the scenes. AI is quietly transforming supply chains – forecasting demand, reducing waste and keeping shelves stocked. Every transaction, every scan and every delivery feeds intelligent systems that provide actionable insights, enabling retailers to plan better, minimise errors and maximise sales.
This is the route Starbucks has taken – announcing that it will use AI to help baristas recall recipes, manage rotas and automate inventory counts. While Just Eat has captured attention at the front of house; Starbucks’ use case points to where AI can deliver real lasting operational impact.
While customer-facing AI may dazzle, it rarely addresses retail’s hardest problems including unpredictable demand and inaccurate stock data. A polished chatbot won’t fill an empty shelf. But AI-powered supply chains, powered by trusted, accurate data, just might.
Translating data into business outcomes
Recent years have exposed just how fragile global supply chains can be. From shipping disruptions in the Red Sea to tariffs and labour shortages, volatility has become the norm rather than the exception.
In fact, a 2026 NVIDIA study found that 64% of respondents reported increased supply chain challenges from 2024 to 2025. In response, 75% plan to increase spending on supply chain AI in the coming year, with over half prioritising operational efficiency and throughput.
However, success in this environment requires more than reacting to disruption – it demands anticipation. Retailers must use real-time data across their ecosystems – sales patterns, supplier performance, logistics networks and customer behaviour – to spot emerging trends, predict volatility and adjust operations proactively.
Predictive models can simulate what-if scenarios and assess their impact across the supply chain, stress-testing operations before disaster strikes. What happens if a key supplier misses a shipment? If a port closes unexpectedly? If demand spikes by 30% in one region? Automated systems can respond in near real time, rerouting shipments, rebalancing inventory and flagging supplier risks before they escalate.
Whether its responding to a sudden heatwave-driven spike in iced coffee sales, anticipating a viral social media trend orforecasting seasonal pumpkin spice demand, agentic AI enables faster, smarter decisions, turning data into tangible business gains.
The opportunity, however, extends well beyond profitability. In the UK alone, retail generates an estimated 1.1 million tonnes of waste each year, much of it food related.
Inaccurate forecasting, surplus stock and inefficient logistics not only erode profit margins but also exact a heavy environmental toll.
AI offers a transformative solution. By predicting demand with precision, monitoring inventory in real time, and optimising delivery networks, it prevents overproduction, reduces emissions, and turns surplus stock into opportunity through redistribution.
Retailers that embed AI intelligence across their operations don’t just cut costs – they lead a new era of low-waste, resilient and environmentally responsible retail.
The data reality check
Of course, AI is only as effective as the data that powers it.
While many retailers are investing in predictive analytics (40%) and automation (50%), Qlik research shows that 39% still admit their internal data is limited or incomplete. In a world where challenges unfold faster than ever, organisations need access to high-quality, trusted data at their fingertips.
It’s this foundation of quick and reliable data that unlocks the real potential of AI across the retail supply chain.
Investing where it matters
To be clear, customer-facing AI tools – like Just Eat’s chatbot – have their place. They can add convenience and createthose all-important fun moments of engagement for consumers. But when it comes to real competitive edge, the best applications for AI lie behind the scenes. Retailers that use AI to turn data into action can build agile, resilient operations that meet demand, respond to trends and operate efficiently and sustainably.
Starbucks’ approach shows how the most impactful AI is often invisible. Its value isn’t measured in novelty, but inoperational resilience, empowered employees and reduced waste – benefits felt across the business and beyond.
Martin Tombs
Martin Tombs is Field CTO at Qlik.
