Retail customer experience is getting an agentic upgrade

Anyone who has ever let the car take the wheel and cruise at freeway speeds has seen agentic AI in action. 

Semi-autonomous vehicles make hundreds of micro-decisions every minute without asking for your input. They can't tell you where to go, but they can help you reach your destination more easily and efficiently. 

Now imagine the same process applied to virtually everything else in your life or work. That's the promise of agentic AI. 

AI agents deployed in business—LLM-powered algorithms that can juggle tasks and their own workloads without human intervention—are set to have a dramatic impact on how work gets done.

These agents are predicted to perform the equivalent of $6 trillion worth of human labor by 2030, according to The Futurum Group. Once deployed, their influence will be felt in dozens of major industries, from finance and healthcare to government and manufacturing. 

One of the first sectors where agentic AI will make a dent is retail and ecommerce. According to one recent study, 75% of retailers believe AI agents will be essential for keeping pace with their competition, and more than 40% are currently piloting the technology.

"The future of retail lies in strategic integration of agentic AI, paired with human expertise,” says Lauren Lee, senior director of CX sales at Freshworks. “The challenge for retailers today isn't about resisting AI adoption—it's about identifying the right entry points."

Just as consumers have grown used to AI-driven product recommendations when they shop online, next-generation AI agents are being prepped to manage customer interactions, forecast demand, manage supply chains, and more.  

Here’s a breakdown of how agentic AI is evolving across the sector. 

Customer support: High volume, high expectations

No retailer wants to deliver a poor customer experience. But when they do, it can be devastating to their business. Two out of three consumers will abandon a brand after just one bad experience, costing retailers upwards of $3.7 trillion each year.  

Agentic AI will play a starring role in solving that problem. Gartner predicts that by the end of this decade, 80% of customer interactions—from checking the status of orders and deliveries to automatically processing returns and refunds— will be handled by AI agents. 

It’s a win for everyone involved. Consumers get their questions answered faster with fewer hassles, while retailers can shave up to 30% off their operational costs, notes Gartner. 

For example, after UK-based retailer Hobbycraft began using Freshworks’ AI-powered support solution, it was able to successfully resolve 82% of all customer support tickets at first contact. A third of those tickets are now handled by an AI agent, with Hobbycraft service reps using AI co-pilot features to quickly resolve the rest. Customer satisfaction ratings are also up 25% with the new system, says Simon Birch, Hobbycraft’s customer service manager. People will always have the option to speak with a service representative, adds Birch.

“AI is helping answer questions without the need for a human agent,” he says. “Summarizing interactions for service reps is fantastic not just for saving time but also helping them generate more detailed responses."

Read also: How Broad River Retail is creating new customer support roles to manage AI teammates

Intelligent agents are especially good at process-driven jobs like customer service, says Rob Whiteley, CEO of Coder, a provider of cloud development environments. Increasingly, human and digital agents are working side by side, with service reps spinning up agents in the background to find answers more quickly.

"We’ve all been playing with customer service chatbots for a long time, but agentic takes that to a whole new level,” says Whitely. “Rather than just handing a chatbot a universe of potential answers to draw from, you’re giving an AI agent creative license to work out how to solve the problem. It’s a much better user experience.”

Demand forecasting: Raising the IQ of the retail supply chain 

Predicting consumer demand has always been an enormous challenge for retailers. Order too little of a product and it goes out of stock, costing sales and sending customers to competitors. Order too much and the product sits on store shelves, tying up cash that could be better spent elsewhere.

Managing the supply chain so that you always have the right products in stock is a universal pain point for retailers, notes Andrew Lokenauth, business strategist and author of a popular newsletter on personal finance. By analyzing point-of-sale data, seasonal trends, local weather, in-store promotions, and other factors, agents can determine when certain products are running low and automatically order more.

Lokenauth says he recently helped a large electronics retailer deploy AI agents to manage its supply of smartphone cases, charging cables, and wireless earbuds. After six months, the Pacific Northwest–based chain was able to reduce the number of out-of-stock situations by 23%.

Before deploying AI, the retailer was warehousing 12 to 15 weeks' worth of smartphone accessories. Intelligent agents allowed it to slash that inventory in half, reducing costs for storage and insurance while providing a boost to cash flow. Agents also freed store managers from having to manually check stock levels, says Lokenauth. 

Read also: Shep Hyken on why agents need AI more than customers

“Retail AI agents are already getting scary good at predicting demand patterns, and will likely master supply chain optimization in two to three years,” says Lokenauth. “If you can confidently reduce your inventory levels while maintaining or improving service levels, that’s when the real savings kick in.”

Personalized experience and dynamic pricing: Emerging opportunities

Retailers often struggle to deliver an experience that speaks directly to each shopper. Research shows that 75% of consumers expect to have personalized interactions with their favorite brands, and become frustrated when that doesn’t happen. That’s a big reason why companies that succeed at personalization grow 40% faster than those that don’t, according to McKinsey research.

Agents can help retailers deliver more bespoke experiences. For example, online vendors will deploy agentic AI to deliver personalized branding to thousands of customers at once, says Dawson Whitfield, CEO and co-founder of Looka, an AI-powered branding and design firm. 

"Agents can automatically change a retailer's visual identity to match the audience it wants to attract—say, neon accents for Tokyo streetwear fans or earth tones for Portland hikers—while still maintaining core brand identity," Whitfield says.  

Looka's ecommerce customers are already using AI to A/B test thousands of product visuals in days instead of months, he adds, driving up click-through rates by 25%. 

Dynamic pricing is another area where agents can excel. By monitoring competitors' ecommerce sites and anticipating consumer demand, agents can adjust product prices to match market conditions.

A good use for agents is analyzing how new products are performing and suggesting micro-adjustments to placement, pricing, and promotions, says Kate O'Neill, founder of KO Insights and author of What Matters Next: A Leader's Guide to Making Human-Friendly Tech Decisions in a World That’s Moving Too Fast. 

But the key to success with agentic AI is knowing when to allow agents free rein and what decisions require human accountability, O'Neill explains. Every agentic system needs explicit guardrails around how autonomously agents can be allowed to operate.

"The retailers who struggle typically blur the lines of accountability, designing systems where neither humans nor AI have clear ownership of decisions," she warns. If you optimize for efficiency without considering the moments that drive customer loyalty, your agentic AI efforts are likely to fail."