The art of merchandising has always been rooted in creativity, intuition and a deep understanding of the customer. Advances in agentic AI are amplifying this by allowing merchants and planners to delegate manual, repetitive work to AI tools, freeing them up to focus on creative decisions. In fact, McKinsey’s January 2026 Merchants unleashed: how agentic AI transforms retail merchandising report suggests retail merchants could reclaim up to 40 per cent of their time by offloading these tasks to agentic AI.
“Earlier generations of AI gave merchants better dashboards and faster analytics, but agentic systems go a step further by taking action,” says Sue McMahon, merchandising, sales and revenue growth strategy lead at Microsoft. “They can monitor signals, refine assortments, adjust pricing and enrich product data, all within the guardrails set by the merchant. Agentic merchandising represents a fundamental shift in how AI is used within retail. In practice, this means a retailer’s merchandising function starts to operate more like a continuous intelligence system. For example, an agent could track real-time demand signals overnight, spot a change in category trends, identify an inventory imbalance and prepare a prioritised recommendation brief for the merchant to review the next morning. Tasks that once took teams days to consolidate can now happen in minutes.
“At Microsoft, we see agentic merchandising evolving across three layers. Firstly, agents that handle repetitive, data-heavy tasks such as catalogue enrichment, demand forecasting analysis and promotional reporting. Secondly, agents that orchestrate workflows across systems, linking merchandising decisions with supply chain, store operations and customer experience in real time; and thirdly, agents collaborating with one another, while the merchant remains the strategic decision-maker overseeing the process.”
McMahon believes agentic AI is fundamentally reshaping how decisions are made across the retail sector. “At the task level, agentic AI is a powerful accelerator,” she says. “Processes to pull together sales data, run forecast models and prepare vendor negotiation briefs once took a week to complete, but now they happen continuously and automatically. That is acceleration. However, we are witnessing a more fundamental shift at the structural level.”
Historically, merchandising models were based on weekly or monthly decision cycles and anchored to static reporting rhythms; agentic AI breaks that cadence. Decisions can now be triggered dynamically by factors such as a predicted weather change, a sudden surge in social media interest for a product or a competitor move, allowing merchandisers to act in real time.
“The most valuable skill is no longer synthesising data manually; it’s knowing what questions to ask, setting the right guardrails for agents and applying the commercial and cultural intuition that AI simply cannot replicate,” says McMahon. “This new merchant profile has been described as ‘strategic orchestrator’ by McKinsey. It is someone who directs AI agents, guides assortment strategy across channels and spends their freed-up time on supplier relationships, customer insight and brand-building.
“That said, we should be clear-eyed: the shift is happening, but the pace varies enormously across the industry. A retailer with clean, unified data and strong AI governance can start capturing value now, while a retailer with fragmented legacy systems and siloed data is still largely in the acceleration phase. The technology is ready; the readiness of the organisation is often the bigger hurdle.”
Several retailers are using agentic AI tools to support merchandising operations at scale. Walmart has built a suite of AI tools to help buying teams with sales analysis, inventory forecasting and assortment decisions, reducing the time they spend on manual data work.
Walmart's merchant assistant named Wally is part of the store’s suite of agentic AI tools and helps reduce time spent on manual data work
UK retailer Marks & Spencer has worked with Microsoft to deploy a total of 11,000 Microsoft 365 Copilot licences – one for every store manager and support centre colleague. By embedding AI across its systems, Marks and Spencer intends for AI agents to support stock forecasting and ordering, generate marketing materials and power a colleague-help hub. Additionally, the retailer reduced machine learning model execution time by 50 per cent by using Azure, which has directly improved the speed of the M&S Sparks loyalty personalisation engine.
US clothing company Guess is piloting Microsoft Copilot Studio-based catalogue enrichment to automate product onboarding, categorisation and metadata normalisation. It aims to transform spreadsheet-based merchandising processes into structured product content capable of supporting discovery, recommendations and a personalised shopping experiences at scale.
“What ties these use examples together is the idea of agents taking over the high-volume, data-heavy work that has traditionally taken up so much of a merchant’s time,” says McMahon. “That frees up merchants to focus on the strategic judgement calls and creative decisions that really set a retailer apart. If implemented poorly, AI can dilute merchandising creativity, but the opposite is also true: done well, agentic AI can amplify creativity. The most creative acts in merchandising – such as identifying an emerging trend before the data shows it, curating an assortment that says something meaningful about a brand, building a supplier relationship that unlocks differentiated product – all those things require human judgement, cultural fluency and emotional intelligence, which no AI agent can replicate.”
In keeping with its ‘Copilot, not autopilot’ philosophy, Microsoft aims to keep humans at the centre of AI systems. As such, every agentic capability has been designed to generate recommendations and flag low-confidence decisions for humans to review.
This philosophy extends to Microsoft’s partner ecosystem, where McMahon believes “the most exciting innovation” is taking place. One partner making notable progress in helping retailers to modernise merchandising is Accenture-Avanade. The company is applying agentic AI to real-time decisions across pricing, inventory, promotions and assortment planning, helping retailers to modernise core merchandising workflows. These Azure-based systems are designed to interpret demand signals and coordinate actions across merchandising functions, enabling merchants to respond faster on product mix, allocation and promotional strategy.
Marks & Spencer deployed 11,000 Microsoft 365 Copilot licenses - one for every store manager and support centre colleague in the UK
Blue Yonder is co-developing the next generation of supply chain planning agents on Azure AI Foundry with Microsoft’s AI Co-Innovation Labs. “Their focus is on creating AI agents that connect demand signals directly to replenishment and fulfilment decisions in real time,” says McMahon. “The firm was also named Microsoft Global Independent Software Vendor (ISV) Partner of the Year in 2025 – this was the first time a retail and supply chain-focused ISV won that recognition globally.”
Board’s intelligent planning platform applies AI-driven predictive modelling and scenario simulation to merchandise financial planning, which enables retailers to dynamically align open-to-buy, assortment and pricing decisions with real-time demand and financial targets across channels. The platform has improved forecasting accuracy by 10-20 per cent, reduced financial planning time by up to 50 per cent, and enhanced scenario precision by as much as 20-50 per cent.
Fractal, which has over 600 Azure-certified engineers, is also developing solutions for AI-driven demand forecasting, customer analytics and category optimisation. Meanwhile, SymphonyAI is applying predictive and prescriptive AI to core merchandising processes, such as assortment, promotions and inventory planning, with users reporting a 3.5 per cent sales uplift, 10 per cent increase in on-shelf availability, and more than $200 million in incremental annual profit.
“I’m extremely proud of the depth of leadership we’re seeing in our partner ecosystem,” says McMahon.
The biggest obstacle to adopting agentic merchandising is data readiness. McMahon highlights McKinsey research which found agentic AI struggles when systems are fragmented and data is inconsistent. Additionally, research from PwC found 65 per cent of retail executives see data silos as a major barrier to their AI strategies.
“Without a unified, clean and well-governed data foundation that connects point-of-sale, e-commerce, loyalty, supply chain and merchandising systems, even the most advanced AI agents will deliver unreliable results,” says McMahon. “That’s why Microsoft Fabric is such a core part of our strategy, rather than an optional add-on.
“Organisational readiness is another challenge. McKinsey discovered 61 per cent of organisations are either not prepared or only slightly prepared to scale AI across merchandising, and just 24 per cent of merchants say they receive meaningful AI training from their employers. Technology adoption without proper change management and skills development rarely succeeds in the long term.”
McMahon stresses the importance of establishing guardrails before organisations activate AI agents. “Margin thresholds, pricing floors and ceilings, brand standards and vendor agreement requirements must all be codified before agents are given autonomy,” she says. “Otherwise, retailers risk inconsistent customer experiences and reputational damage.”
IDC research suggests for every $1 a company invests in generative AI, they receive $3.7. “The economics are compelling for those who get the foundations right,” says McMahon. “The barriers to implementing and adopting agentic AI are real, and the industry does itself a disservice by talking only about the opportunities without also being honest about the challenges.”
Despite these challenges, McMahon predicts merchandising teams will become more strategic over the next three to five years, with AI agents taking responsibility for data-heavy operational tasks while humans focus on commercial judgement, supplier relationships and brand direction. “My strong belief is that the merchant role becomes more valuable, not less,” says McMahon. “The merchants who thrive will be those who can direct AI agents strategically while applying commercial and cultural judgement and building the supplier and customer relationships that agents cannot.”
According to McMahon, this shift will create entirely new specialisations. Roles such as ‘category intelligence merchant’ and ‘assortment integrity lead’ will emerge to bridge AI-driven insights with brand governance, supplier requirements and category strategy. “These are genuinely new roles that will become important quickly,” she says.
The pace of merchandising decision-making is also expected to change dramatically. Merchants will increasingly work from continuously updated AI-generated recommendation briefs synthesised from overnight sales, inventory, weather and customer data. “The merchant’s job is to interrogate, refine and approve,” says McMahon. “Instead of a Monday morning report, they’ll receive an AI-generated signal brief that has already identified priority actions and ranked them by commercial impact.”
McMahon says Microsoft is particularly focused on innovative AI agents. “One of the areas that excites us most is multi-agent orchestration, where agents across merchandising, supply chain, store operations and customer service communicate and collaborate in real time via open protocols,” she says.
AI is helping retailers shape accurate merchandising models using predicted weather changes, social media trends and insights into competitor behaviour
Microsoft is also investing in what McMahon describes as “digital store intelligence”. Through its collaboration with retail technology company Vusion, Microsoft is exploring how real-time digital representations of physical stores could allow merchandising decisions to be tested and adjusted dynamically at shelf level.
Looking ahead, McMahon believes the concept of a retail frontier firm – an organisation that combines human expertise with AI agents to improve efficiency, accelerate growth and create new value – is closer to reality than most think. “The technology is ready, but the question is whether retailers are willing to invest in the data foundations, the change management and the upskilling to unlock it,” says McMahon. “The goal of agentic merchandising is to give merchants back the time and headspace to do what they do best. Retail has always been a human business at its heart: the relationships with suppliers that unlock exclusive product, the trend intuition that identifies a whitespace in the market before the data confirms it, and the brand sensibility that makes a curated assortment feel intentional rather than algorithmic. These are deeply human capabilities, and they become more valuable as AI takes on the data-intensive work that has historically crowded them out.”
Partner perspectives
We asked Microsoft partners Board and Coretek how they are working with Microsoft to develop agentic AI solutions that allow merchandisers to identify emerging trends and respond with greater speed
“Board’s collaboration with Microsoft focuses on embedding agentic AI into merchandising workflows using the Microsoft Agent Framework on Microsoft Foundry,” said David Marmer, chief product officer at Board. “By combining Board’s unified retail planning platform on Azure with Agent Framework, we enable merchandisers to detect emerging demand patterns, simulate scenarios and act in real time within a continuous planning environment. These AI agents go beyond insight by recommending and orchestrating next-best actions across assortment, pricing and allocation, while keeping decisions aligned across merchandising, supply chain and finance. The result is a more intelligent, adaptive approach that helps teams anticipate change, reduce risk and execute with greater speed and confidence.”
David Marmer
Chief Product Officer, Board
“Coretek helps retailers harness Microsoft’s agentic AI to identify emerging trends and respond with market-leading speed,” said Brian Barnes, chief technology officer at Coretek. “Using Microsoft Azure AI Foundry, real-time data pipelines, we developed agents that continuously analyse social signals, purchasing behaviour and inventory dynamics to surface actionable merchandising intelligence. A large speciality retailer in the south-east US deployed an autonomous AI agent that flagged trending product categories and triggered replenishment workflows in real time – reducing time-to-shelf by 40 per cent and improving gross margin by 15 per cent. Merchandisers now lead trend strategy instead of chasing data, creating lasting competitive advantage.”
Brian Barnes
Chief Technology Officer, Coretek
Discover more about agentic AI and insights from experts at Microsoft Partner businesses including ServiceNow, Intermedia and AVEVA in the Summer 2026 issue of Technology Record. For more content like this, subscribe to the print edition or free digital edition of the quarterly Technology Record magazine.