Retailers today face higher pressure than ever to streamline and scale and while meeting growing customer expectations. AI agents in retail are emerging as critical tools to automate and enhance key workflows without losing precision.
In this article we discuss:
Few industries undergo as much change as retail. From maintaining visibility in crowded markets to delivering personalized customer experiences, retail leaders are often at the forefront of technological innovation. While conventional artificial intelligence (AI) excels at data analysis and prediction, it requires human insight to actually apply action and intelligence. Agentic AI is changing that.
AI agents in retail can analyze context, make decisions, and act autonomously across complex value chains. In turn, retailers can scale as needed with agility and confidence, all while refocusing human teams on more strategic work.
Agent adoption in the retail industry is accelerating: 42% of retailers have already deployed agents and another 53% are evaluating use cases. Meanwhile, 70% of consumers also say they’d welcome agents to help them optimize their shopping experiences.
Real world use cases for retail agents are diversifying as adoption expands, and leading organizations are already embracing what agents can offer. To stay competitive, it’s critical that retail companies understand the full extent to which AI agents can support their future success.
Today 95% of retailers have either piloted agents (42%) or are exploring potential agent use cases (53%) for their organizations.
AI agents combine all the capabilities of traditional AI tools with autonomous analysis, decision-making, and action. AI agents for retail can execute end-to-end workflows like inventory restocking, refining promotions, and guiding customer interactions—all with minimal human oversight.
Agents ingest real-time data from across channels, apply business rules, and trigger actions automatically, transforming standalone AI models into continuous, adaptable, self-driving systems that adjust to changing market conditions.
Retailers are often positioned more readily for adoption thanks to their use of ERP and point-of-sale systems, often orchestrated on the cloud for centralized data management. With a strong data foundation set, retailers can deploy agents with speed and confidence.
Those that do are seeing tangible benefits and business impact in key areas like:
The initial shift towards agent-driven retail is laying the groundwork for scalable innovation. As AI agents mature and integrate further, retailers can expect accelerated ROI, greater operational agility, and enhanced AI-powered customer experiences that drive competitive advantage and steady growth.
In retail, agentic AI unlocks new opportunities by embedding intelligence directly into core processes. Below, we explore four critical AI agent use cases that are already changing AI in retail—from streamlining supply chains to enhancing on-the-ground customer support.
Using live market intelligence, customer engagement signals, and predefined margin thresholds, AI agents autonomously calibrate pricing structures and orchestrate promotional campaigns across different channels. They can adjust discounts, reallocate promotional budgets, and schedule targeted flash sales in real time to achieve maximum revenue capture during high-demand windows without manual intervention.
Agents can then continuously learn from campaign outcomes, refining parameters to boost ROI and maintain competitive positioning. This capability was a top talking point at Shoptalk Europe 2025, one of EU's leading annual retail events. Unlimitail CEO Alexis Marcombe called agents a "game changer" for structuring campaign data and optimizing overall management.
"You just have to ask what you want your agent to do," Marcombe noted, "and it will be delivered."
By embedding AI agents in websites, mobile apps, and kiosks, retail companies can create users with dedicated virtual assistants. Agents can guide shoppers with product discovery, styling recommendations, and voice-driven interactions, blending conversational AI with backend systems to personalize customer journeys.
At the aforementioned Shoptalk Europe event, General Manager for Global E-Commerce at L'Oréal, Mark Elkins, explained how agents will play a role in reading product descriptions and using it to guide consumers in the right direction.
To optimize visibility, brands will need to add experience context in addition to functional descriptions. Elkins used the example of an SPF product, which, instead of a simple ingredients listing, might also have to include text about "going on holiday" that agents could scan and align with consumer buying intent.
In some cases, like that of retail giant Walmart, retailers are even looking beyond personalized recommendations, exploring agents that autonomously manage shopping lists and replenish items based on learned user preferences.
Agents enhance physical retail by continuously evaluating store layouts against sales performance, traffic patterns, and inventory data. They can recommend optimal product placements, adjust shelf configurations, and trigger promotional display updates automatically to both drive higher sales per square foot and improve shopper experiences.
AWS dubs the concept "The Agentic Store", where agents can, for example, monitor stock levels and take actions like automatically triggering restocking tasks or adjusting electronic shelf labels. By using customer data effectively, agents can make products more discoverable and provide personalized product recommendations that convert at a higher rate.
Agents serve as first-line responders to customer inquiries across chat, email, and social channels—automating routine support tasks such as order status updates, return authorizations, and FAQ resolution. By integrating context like CRM data and sentiment indicators, customer service agents can personalize interactions and escalate complex issues to human agents when needed.
Finding the right balance between answering questions quickly with AI and human intervention is key. Walmart is again a leader in this area, highlighting its own commitment to using agents as a way to improve service response, quickly route inquiries, automate the "mundane," and loop humans in when needed to handle more complex issues.
Retail giants like Walmart and Amazon are leading on varied use cases where AI agents make an impact.
As AI agents evolve from pilots to core components of retail operations, they'll increasingly power decision-making—from inventory management and pricing to customer engagement and supply-chain orchestration (and more).
Retailers that act on this shift can stay ahead of the curve by embedding agentic frameworks into their digital roadmaps now. Successful preparation requires more than technology deployment; it demands domain expertise in retail processes, data architecture, and change management.
Partnering with a seasoned AI specialist ensures you not only select the right AI solutions but also tailor agent behaviors to your unique workflows. Expert guidance accelerates implementation, mitigates risks, and provides governance frameworks that uphold brand standards and regulatory compliance.
With a proven methodology and expertise to support deployment, you can pilot agents quickly, measure results rigorously, and scale with confidence so your retail organization can harness agentic AI to its fullest potential.
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