Retail and consumer goods companies are under growing pressure to move from concept to execution at unprecedented speed, with viral trends driving the purchases of seven in ten consumers, according to a 2026 survey by automated warehouse fulfilment firm, Locus Robotics. The survey findings highlight how viral demand and operational uncertainty compress planning cycles, forcing retailers to make their enterprises more responsive, agile and resilient.
By utilising platforms and ecosystems delivered by Microsoft and its partners, retail and consumer goods organisations are closing the gap between concept and execution. Companies are redesigning their operating models to embed AI-driven intelligence, real-time data-sharing and automation into every decision point across multiple departments, including research and development, manufacturing and supply chain operations. AI enables data, decisions and workflows to be connected into a shared intelligence layer, which inks cloud insight with physical operations to ensure the right products reach stores and online channels when consumers want them.
“Speed‑to‑shelf has shifted from a competitive advantage to a non‑negotiable requirement,” says Felice Miller, global business strategy lead for retail and consumer goods at Microsoft. “Consumers move in real time, trends ignite and fade overnight, and disruption is constant. Retail leaders now have to ask a hard question: is our operating model truly built to sense change, make decisions, and execute at the speed the market demands. There are numerous ways organisations can test if their operating model is truly built for rapid change, but every gap identified is an opportunity to strengthen the enterprise and build the intelligence, agility and resilience required in a world where speed is the default expectation.”
Delays in progressing ideas from conception to customer delivery are often caused by fragmented data, unrealistic planning and slow execution by cross-team hand-offs. “Microsoft’s three IQ intelligence layers remove this friction by unifying data, accelerating decisions and automating workflows across departments, such as research and development, manufacturing and supply chain,” says Miller. “When organisations unify data, simulate continuously and automate workflows, speed and execution improve dramatically, but optimisation is an ‘evergreen opportunity’ which should never be considered complete; it’s ongoing as targets and the business evolves.”
Microsoft’s Fabric IQ addresses the challenges of fragmented data by enabling scenario analysis and confidence‑aware decisioning. Foundry IQ uses AI-driven scenario testing to help teams make earlier, more confident decisions and continuously adapt as signals change. Work IQ turns manual hand-offs into automated workflows, while Agent365 ensures AI agents operate within clearly defined guardrails, so organisations can move from insight to execution faster.
One company using Microsoft technology to move from insight to execution is Estée Lauder Companies, which operates nearly 25 luxury beauty brands across 150 countries. In 2025 the firm worked with Microsoft to develop an AI agent, ConsumerIQ, using Microsoft Copilot Studio and Azure OpenAI Service. The tool analyses documents, identifies trends and provides recommendations, reducing the time required to gather information from weeks to minutes. This allows Estée Lauder to respond faster to emerging trends, launch products more quickly, and strengthen customer engagement and brand loyalty worldwide.
Estee Lauder’s AI agent, ConsumerIQ, enables the company to respond faster to trends and launch products quickly to meet customer demand
Meanwhile, beer and beverage producer Carlsberg teamed up with Microsoft to build ‘Global Brain’, an AI-powered knowledge assistant for its supply chain teams. The solution runs on Azure AI and Azure OpenAI Service in Foundry Models to provide natural language search and context-aware responses enabling over 10,000 employees to retrieve supply chain knowledge quickly – it reduced the time spent searching for information from 30 minutes to a few seconds. With guidance from Microsoft Unified and Azure cloud infrastructure, the system was developed in just two days.
Carlsberg worked with Microsoft to build an AI-powered assistant on Azure AI and Azure Open AI Service to help supply chain teams find information in seconds
Kraft Heinz Company is also using Microsoft technology to improve efficiency. The firm, which has manufactured food and beverage products for 150 years, teamed up with Microsoft to create an AI agent using Azure OpenAI. The Cookbook, which is currently being piloted at a US production facility for Heinz Tomato Ketchup, enables employees to more easily analyse production data, including batch thickness and colour, improving efficiency.
Kraft Heinz Company is piloting the AI agent Cookbook at a US production facility with the aim of monitoring and analysing batch thickness and colour
To move from insight to execution at speed without sacrificing accountability or customer trust, retailers must design AI systems that allow speed and responsibility to “reinforce” one another, according to Miller. “The most effective approach is a human-in-the-loop by design model, where risk determines autonomy and technology provides transparency at every step,” she explains. “In this model, low-risk processes can be automated within defined guardrails; medium-risk decisions use AI to generate recommendations with human approval; and high-risk scenarios remain human-led, with AI acting in an advisory role.”
Agent365 operationalises these risk tiers while Fabric, Foundry and Work IQ act as governed capability layers to ensure decisions like reducing the price of a seasonal product line to clear the stock before the end of a quarter bring about the best results for retailers. This is achieved through scenario testing and drift validation where production data is monitored to prevent issues like over or understocking.
“Retailers and consumer goods organisations don’t have to choose between speed and trust; with IQ-based guardrails, they can move fast where it’s safe, be human-led where it matters and be fully accountable everywhere else,” says Miller. “Once intelligence is embedded across all departments, retailers will be tempted to measure success by familiar metrics, such as speed or return-on-investment, but agent-based operating models really change the nature of what success looks like. The real question now becomes less about a single, measurable key performance indicator, but more about how quickly the organisation can learn and adapt.”
Additionally, retailers are under pressure to grow their business while reducing their carbon footprints and de-risking supply chains. “These priorities are increasingly intertwined,” says Miller. “Growth, decarbonisation and resilience are no longer trade-offs to manage but forces that reinforce one another when every decision is informed by data. Microsoft’s partner ecosystem is a force multiplier; when combined with Microsoft’s IQ platform, our partner model becomes a powerful, competitive engine, expanding capability and accelerating time to value, while also giving retailers access to innovation they could never build alone.”
Through a partnership with Microsoft, Danone launched a global upskilling programme and deployed Microsoft 365 Copilot and autonomous agents to automate human resources and order-to-cash processes in order to boost competitiveness and growth. Empowering employees with digital skills and integrating AI across global operations enabled the French multinational food and beverage company to reduce manual errors, speed up order handling, cut billing disputes, improve cash flow and foster innovation.
Microsoft partners, including 09, Auger, Blue Yonder, Fractal, IBM/Neudesic, Lyric, Nvidia, Sight Machine and Symphony AI, use flexible architecture to extend the Microsoft stack to provide retail and consumer goods–specific functions, such as demand planning and store automation, that accommodate industry governance frameworks. Agent365 ensures partners can build AI agents that operate safely and consistently across stores and regions. “Our partners are focused on outcomes, not technology,” explains Miller. “They give retailers the breadth, speed and intelligence to lead the market, not with one monolithic system but with a composable, continuously innovating system of intelligence powered by the IQs. They bring playbooks and value engineering that tie IQ-powered solutions to concrete business results.”
Miller suggests retailers judge success by measuring how quickly they move from signal to decision and from decision to impact. “When autonomous systems resolve more operational issues on their own, it reflects more than efficiency gains,” she explains. “The enterprise becomes significantly more responsive to events as they unfold in real time.”
Trust is another key metric. Retailers must have confidence in the agents supporting their operations, which requires them to evaluate forecast accuracy, recommendation acceptance rates, override frequency and audit transparency. Consistently correct and documented decisions allow organisations to integrate AI more deeply into daily operations.
“The most meaningful measure of success may be how quickly the organisation itself learns,” says Miller. “Using Enterprise IQ, retailers should observe how rapidly models improve, how many processes transition to agent-driven execution and how quickly new use cases can be deployed. If a capability that previously required six months to launch can now be delivered in six weeks, it signals a step change in the enterprise’s ability to innovate and adapt, which is the ultimate definer of success.”
Miller believes the gap between retail innovators and laggards will widen in the next few years. “Leaders will build a real-time, data backbone that brings operational and external signals into one platform,” she says. “They will also deliver decisioning services through reusable APIs and collaborate across supply ecosystems with partners and logistics providers. Stores and distribution centres will become more event-driven environments where signals trigger actions automatically. The most effective organisations will build carbon awareness and compliance into operational planning, so environmental impact becomes part of everyday trade-offs rather than an afterthought. Success ultimately depends on people and organisational design, not just on technology.”
To ensure today’s investments support tomorrow’s needs, retailers should prioritise strong foundations, building for composability, with open APIs, event-driven systems and clean, shareable data. This will enable capabilities to evolve and integrate over time, creating continuous learning loops, where each release improves the system’s intelligence.
“We are entering the first era where the enterprise itself can learn, and that changes everything,” says Miller. “AI is often discussed in terms of efficiency, speed or cost, but its real impact is enabling organisations to continuously learn and adapt. The retailers that succeed will design for compounding intelligence, shift leaders from operating the business to setting direction while intelligent systems handle the micro-decisions and prioritise adaptability above any single metric. Ultimately, adaptability will define the retailers that lead the next era of intelligent enterprise.”
Discover more insights like these in the Spring 2026 issue of Technology Record. Don’t miss out – subscribe for free today and get future issues delivered straight to your inbox.