For brands and retailers, success isn’t just about running assortments or managing seasonal demand. It’s about making the right decisions more quickly and consistently in increasingly complex operations. In this scenario, the ability to step back, prioritize what matters, and act with precision has become an important differentiator.
In 2025, one topic has constantly shaped these strategic discussions: Agentic AI. According to Gartner, AI agent-related queries increased by more than 750% in 2024, and by 2029, half of everyday business decisions are expected to be made autonomously by AI agents, up from just 20% today.
Additionally, Gartner also claims that agentic AI represents the “next evolution of AI maturity,” moving from automation to autonomous, results-driven operations.
Agentic AI in Retail becomes a self-learning decision layer that extends across supply chain, sales, pricing, operations and customer experience (CX).
However, the real quest is no longer whether agentic AI will transform retail, but rather how retailers can use it to achieve tangible benefit, turning intelligence into rapid decisions, greater agility and measurable impact across the organization. Let’s go.
Embracing Change: Top Agentic AI Use Cases in Retail to Get Ahead of the Agentic AI CurveDid you know that 77% of global retailers now believe that autonomous decision-making will be the biggest differentiator in retail performance over the next five years. So, with that in mind, let’s look Top Use Cases for Agentic AI in Retail which brands should focus on in 2026.
#1 Hyper-personalized shopping, at the pace of the agentsIn 2026, personalization goes far beyond product recommendations or segmented campaigns. Agentic AI in Retail enables individual customer agents to learn preferences, context, intent and timing in real time.
These agents curate assortments, content, offers and channels tailored to each shopper, through app, web, in-store and even voice commands. Rather than simply waiting for a customer to browse or search, the agent takes the initiative to guide the shopping experience, predicting needs and guiding decisions at the right time.
Impact:
Increased basket size, higher conversion rates and deeper loyalty, without the emphasis on manual campaign planning.
#2 Dynamic pricing that thinks and reacts autonomouslyWith shelves filled with numerous products, choosing the appropriate price is never easy. How will buyers know whether or not they got a better deal? Indeed, Agentic AI systems are the solution to streamline the process of personalized promotions and pricing. With effective customer segmentation, you can leverage our RGM suite with agentic capabilities to:
Promotion planning – Analyze price elasticity and competitor actions to eliminate overly aggressive discounts and improve promotional impact.Custom Pricing – Offer loyal customers discounts on their purchased items or tailor promotional pricing for new buyers.Price optimization – Apply guardrails to avoid overpricing, underpricing, or competitive positioning while maintaining maximum profits.Impact:
Faster response to market volatility, improved margins and less revenue leakage caused by late decisions.
#3 Predictive and self-correcting inventory managementInventory has always been one of retail’s most difficult problems and one of its largest cost centers. With agentic AI, retailers can integrate inventory agents that detect risks early, forecast demand, and act autonomously throughout supply chains.
These agents constantly rebalance inventory across locations, adjust fulfillment routes, trigger replenishment, and even renegotiate suppliers in real time. When demand changes unexpectedly, the system adapts, without waiting for human intervention.
Impact:
Lower carrying costs, reduced overstocks and out-of-stocks, and higher on-shelf availability.
#4 End-to-end customer support that resolves, not escalatesThink about Agentic AI in Retail This way: They respond to customer queries on the front line via chat, email and social media, automating daily support tasks such as order status updates, resolving FAQs and returns. By integrating sentiment indicators and context like CRM data, customer service agents can escalate difficult issues to human agents and personalize interactions as necessary.
The key is finding the right balance between answering questions quickly with AI and human intervention. Walmart is a leader in this area, emphasizing its commitment to using agents to quickly improve service response, route requests, automate “mundane” tasks, and bring in humans when needed to handle more complex issues.
Impact:
Fast resolution times, reduced support costs and measurable improvement in customer satisfaction.
#5 Machine-to-machine tradingOne of the rudimentary changes coming is the emergence of machine-to-machine trading. Consumer AI agents, representing buyers, will increasingly interact directly with agents for retailers and brands.
These agents are responsible for negotiating prices, comparing different options, managing subscriptions, checking availability and making purchases autonomously, based on the preferences defined by the user. Retailers with ready-made systems will succeed in these negotiations, not through marketing spend, but through smarter, faster decisions.
Impact:
Higher repeat purchases, frictionless shopping, and strong long-term loyalty.
#6 Proactive Decision Making in Retail OperationsAt the company level, Agentic AI in Retail becomes a decision orchestration layer. Pricing, merchandising, supply chain, marketing, and customer experience agents continuously collaborate to resolve tradeoffs in real time.
Instead of leaders reacting to dashboards, agents take actions, make decisions, and only bring the human into the loop when necessary. This approach creates a retail business that constantly learns, adapts quickly and operates with resilience.
Impact:
Better cross-functional alignment, improved agility, and scalable operational excellence.
ConclusionWhat you have just experienced is more than a shift in the technology space; this is a fundamental rethinking of how these zones impact the retail space.
HAS Polestar Analysiswe help retailers make this transformation a reality. We combine expertise in strategy, systems and agentic AI to design intelligent operations that unlock measurable and sustainable benefits. Contact us today.