Over the last decade, I’ve watched the customer journey transform numerous times. From in‑store only to desktop and then mobile, we’ve steadily moved toward shopping “everywhere, anytime”. With these advancements, new capabilities have emerged like BOPIS, inventory visibility, search, social discovery, and ratings into the everyday experience. Each wave accelerated faster than the last as customers grew more comfortable with new capabilities and made them habits. As we navigate this evolution, the role of AI in retail customer experience becomes increasingly vital.

We’re now in the next great leap: shoppers are turning to AI to cut through the noise and help them make shopping decisions.  AI is going beyond improving efficiency; it’s driving measurable results. In fact, 69% of retailers using AI report increased revenue, reinforcing its growing role in shaping customer experience and business performance.

Our recent research backs this up. Fifty-eight percent of shoppers made a purchase based on an AI recommendation, and 91% either purchased or seriously considered a purchase after AI input. But AI’s role is different from past digital channels: it excels in planning, discovery, and comparison, especially where choices and stakes are high. It helps shoppers make decisions with confidence. 

But AI isn’t acting alone. While it’s great at narrowing choices, retail expertise is what reassures shoppers they’re making the right decision. AI provides retailers with deep product knowledge, transparent policies, and trusted reputation. Retail brands who can clearly express that authority will be the ones shoppers choose. 

AI in retail customer experience benefits are a two-way street for both consumers and retailers.  Consumers get faster access to relevant information, while AI helps surface retailers’ expertise, empower employees, and elevate the customer–retailer interaction.  So when retail employees wonder “will AI replace me?”, it’s actually going to unlock more time for them to do meaningful, higher-impact work. 

How shoppers use AI today 

Understanding the impact of AI in retail customer experience helps retailers adapt to meet shopper needs effectively.

Shoppers lean on AI in retail customer experience most in high-consideration categories where the stakes are greater, and the number of choices can feel overwhelming. Forty-eight percent of consumers used AI for price comparisons in electronics, and 36% looked to AI for apparel inspiration. In planning-heavy moments (hosting, décor, special-occasion attire), shoppers used AI for ideas and comparisons far more than instant checkout. Only 5–6% completed purchases directly through AI platforms.  

That aligns with my own recent shopping experience. I used AI to narrow down options for a new wearable health device that needed to be comfortable, stylish, and capable of meeting specific health-tracking needs, without breaking the bank. Not long ago that process would have meant reviewing numerous product pages, social posts, reviews, and prices across multiple sites. Now AI can gather, consolidate, and offer personalized recommendations and pros and cons for each in seconds.  

That’s the pattern that is playing out more broadly. AI is compressing the most time-consuming part of the shopping journey from product discovery, comparison, and early evaluation with fewer touchpoints for the consumer.  

During my time in e-commerce retail, I remember how much effort went into improving product discovery: better search, richer content, clearer filters, and more helpful reviews. I think about how AI in retail customer experience today is using that product data, content, and consumer provided information like ratings & reviews, user-generated insights, and more to pull together those recommendations for shoppers.  

This shift creates a clear inflection point for retailers. As AI takes on more of the planning and evaluation work, the quality, clarity, and consistency of the information retailers provide increasingly determines how and whether they show up in these new customer shopping journey moments. 

How retailers show up in an AI‑influenced world 

As shoppers increasingly rely on AI to plan and compare, it’s imperative that a retailer or brand’s information is set up to signal to AI that it is the one to recommend. AI won’t create a brand’s expertise—it will surface whatever is already there.  If a brand’s product details, policies, and content are thin, inconsistent, or hard to interpret, AI can’t confidently do that.  

What AI needs to confidently represent a retailer:  

• Complete, structured product fundamentals: Clear attributes, use-case context, compatibility, care, and warranty details—supported by structured data (such as product schema markup) that makes this information machine-readable. AI uses these signals the same way a store associate would to understand relevance and suitability.

• Decision-support content that mirrors how shoppers think: Comparisons, size guidance, FAQs, “best for” framing, and clear tradeoffs. These act as the confidence‑building moments that shoppers traditionally get from expert associates or detailed product pages.  

• Consistent service and policy clarity: Availability, fulfillment options, returns, pickup, and service commitments. When AI pulls these details into recommendations, it reduces uncertainty and shapes which brands shoppers trust. 

• Credible brand signals: Reviews, user-generated content (UGC), accessibility and sustainability claims, and consistent expression of brand expertise and values. AI uses these cues to judge credibility when shoppers ask for “trusted,” “reliable,” “durable,” or “ethical” recommendations. 

As AI reshapes discovery, information quality increasingly determines visibility. In many ways, AI-ready content is becoming the next evolution of SEO. It’s not about gaming algorithms but supplying clean, structured information that AI can interpret accurately.  

Retailers earn trust in AI‑supported experiences the same way they’ve always earned trust in stores: by showing their work. That includes: 

• Reliable product attributes and naming conventions 

• A content supply chain that keeps every SKU complete and updated 

• Structured data that AI systems can parse 

• A single, trustworthy source for policies and service information 

• Governance to keep content fresh as assortments change 

This makes it incredibly easy for AI to understand, trust, and advocate for your brand. 

How retailers prove credibility and expertise in an AI-led journey 

Shoppers increasingly see AI as credible. Forty-one percent say AI recommendations are equal in value to retailer advice, and 38% say they value AI even more. But trust isn’t simply given. Concerns about privacy, accuracy, transparency, and bias remain widespread, often moderate rather than extreme, which means shoppers are willing to engage, but they’re watching closely.  

Retailers earn trust by showing their work: 

• Being transparent about where and how AI is used: Clear labeling of AI‑generated suggestions or automated decisions builds confidence rather than confusion. 

• Citing the data behind recommendations: Whether it’s product information, reviews, or policies, customers expect to know why something was suggested. 

• Explaining the logic (“best for X because Y”): This mirrors how the best in‑store associates talk—specific, contextual, and confidence‑building. 

• Auditing for accuracy, bias, and hallucinations: Shoppers notice when AI gets something wrong. Retailers who monitor quality build long‑term trust. 

• Protecting privacy and giving customers control: Clear consent, control over data, and practical privacy choices reassure shoppers that the value exchange is fair. 

Done right, AI in retail customer experience amplifies brand credibility. And this is where human expertise comes back into the picture. AI can inform and guide, but people validate, reassure, and help customers feel confident in their final decision. 

What I’d do as a retailer: Where to invest AI in retail customer experience for real impact 

If I were a retailer, I wouldn’t go in trying to involve AI everywhere, and I don’t think most retailers think that. But they’re certainly likely overwhelmed wondering whether to start internally or externally… I say both. I’d start with where decisions are the hardest and confidence matters most. This supports both the customer and employee (a win-win). 

1. Prioritize AI where decisions are hardest

I’d focus on high intent, high complexity categories where shoppers face choice overload. AI is most effective at doing the heavy pre‑work. It shortens the journey and gets customers to a point where a meaningful conversation can happen, faster. 

2. Make sure your brand is eligible to show up in those moments

Before investing in new AI experiences, I’d make sure my product and brand information is strong enough to be recommended in the first place. Priority categories need to be clearly described, easy to compare, and supported by consistent product and policy information. If complex categories aren’t well defined, retailers simply won’t appear when customers are deciding. 

3. Equip associates to build on AI research—not repeat it

What’s great about customers arriving having already used AI is that it speeds up the conversation, so associates can pick up where they left off versus starting at the beginning. They should be trained and equipped to ask what the shopper already considered, understand what AI recommended (and why), and identify the missing context AI didn’t capture. Great associates don’t just answer questions. They surface the questions customers didn’t think to ask such as usage, priorities, and what their own customers have shared back with them.  

4. Use AI to support associates in real time 

To make this work at scale, I’d invest in AI tools that put product knowledge, comparisons, inventory visibility, and policy clarity directly in associates’ hands. This will help eliminate time spent searching for information, reinforce consistent brand guidance, and free up mental space for empathy, listening, and personalization. The result is more confident associates and better customer moments. 

5. Redefine success for high-intent and complex categories (your AI pilot categories)

I’d measure success differently in these categories. While improved conversion rates are usually the largest goal, lower return rates and fewer post-purchase issues can also result, along with higher associate productivity, measured by sales per hour and time spent advising vs. searching.  

AI creates efficiency; the retailers who win will reinvest it into higher‑touch service that builds confidence and loyalty. 

The bottom line 

AI in retail customer experience is the largest disrupter in retail’s evolution since online shopping. It’s becoming a planning partner shoppers rely on when decisions are complex and confidence matters. That’s good news for retailers who are willing to do the work: prepare your data, empower your people, and design the handoff between digital guidance and human credibility. 

The brands that win won’t be the ones trying to replace humans with machines. They’ll be the ones who use AI in retail customer experience to clear the path and let their people do what only people can do: connect, reassure, and earn customers for life.