AI in digital commerce works best when it removes friction, not when it adds novelty

Many brands feel pressure to invest in AI. The real question is not whether to use it, but where it can create meaningful value for customers. In digital commerce, that value rarely comes from flashy features alone. It comes from reducing effort, improving relevance and helping people complete what they came to do.

That matters because consumer frustration with digital commerce remains widespread. Across industries, satisfaction is uneven, and the most common complaints are remarkably consistent: poor user experience, weak personalization, incomplete end-to-end journeys, customer service friction, slow or unreliable digital experiences and concerns about privacy and trust. When those issues add up, loyalty is at risk. More than half of consumers say they will switch to another brand after a poor digital commerce experience.

For commerce leaders, this creates a more practical AI agenda. Instead of asking how to add an AI feature to the experience, ask where customers get stuck, where journeys break down and where teams struggle to respond quickly enough. Those are the moments where AI can earn its place.

Start with the friction customers already feel

Consumers consistently signal that they want digital commerce to be easier, clearer and more personalized. They want better content to help them understand products and services. They want more seamless transactions. They want interactions that reflect their needs rather than generic segments. And when something goes wrong, they want help fast.

Customer service issues are one of the biggest sources of friction in digital commerce. Difficulty contacting support, long resolution times and disconnected service experiences can quickly turn a transaction into a negative memory. Other frustrations are just as important: confusing navigation, incomplete product information, weak search, poor site or app performance and journeys that stop short of solving the full problem from discovery through fulfillment, service or return.

Where AI can make digital commerce easier

1. Conversational search that helps customers find the right answer faster

Search is one of the clearest places where AI can reduce friction. Consumers increasingly want search experiences that are intuitive, conversational and connected across platforms. Instead of forcing people to guess the right keyword, conversational search lets them describe what they need in natural language. That is especially valuable in complex categories where customers may not know the exact product name, configuration or terminology.

In travel and hospitality, for example, generative AI-enabled search can simplify a difficult discovery process. Publicis Sapient partnered with Homes & Villas by Marriott Bonvoy to help travelers search for accommodations based on a wide range of specific needs, making it easier to find relevant options without manually sorting through countless listings. That is a strong example of AI creating value through relevance and reduced effort, not novelty.

The same principle applies across industries. In retail, it can improve product discovery. In healthcare, it can help patients locate the right self-service option. In financial services, it can guide customers toward the right tool, offer or next step.

2. Faster issue resolution when service breaks down

When customers have a problem, speed and clarity matter more than cleverness. AI can help brands respond faster by handling common questions, guiding people to the next best action and reducing wait times for routine issues. Natural-language FAQs, AI-assisted chat and triage tools can keep simple service needs from becoming expensive, frustrating escalations.

This does not mean replacing human support with a bot everywhere. Consumer enthusiasm for AI is mixed, especially for conversational assistants. Many people still do not find them especially helpful in purchase decisions, and adoption varies by generation and region. That is precisely why AI should be deployed with care. The goal is not to force automation into every service moment. It is to resolve the right issues quickly and hand off higher-stakes or more emotional issues to people with the right context.

Useful AI support should feel like the fastest path to a resolution, not a barrier between the customer and the brand.

3. Returns, refunds and replacements with less effort

Post-purchase service is one of the most practical areas for AI. Returns, refunds, replacements and appeasements are often high-friction moments for customers and high-cost moments for brands. AI can help automate routine decisions, surface policy guidance, gather the right information upfront and accelerate resolution.

It can also make these interactions more proactive. For example, AI can identify common reasons for dissatisfaction and help prevent them before purchase, whether that means flagging likely fit issues, clarifying expectations or improving information about delivery, availability or policies. In this way, AI supports both service efficiency and better customer experience design.

4. Personalized recommendations that are actually useful

Consumers clearly want more relevant experiences. Across sectors, they ask for personalized recommendations, interactions and tools that align with their preferences and goals. But personalization only creates value when it helps people make better decisions or complete tasks more easily.

That is where AI can improve on older, broad-brush approaches. Instead of relying on static personas, brands can use richer customer data to better understand individual behaviors, preferences and context. This supports more relevant recommendations, offers and content at the right moment.

Still, brands should be realistic. Personalized recommendations alone are not enough to persuade many consumers to share more personal data. The value exchange must be clear. Customers are more likely to respond when personalization is tied to something tangible, such as easier service, faster checkout, more relevant options or better offers. The lesson is simple: personalization should be useful enough to notice, but respectful enough to trust.

5. Dynamic content generation that makes experiences clearer

One of the biggest things consumers want from digital commerce is clearer content. They want better descriptions of products and services, especially in industries where decisions can be confusing or information is fragmented. AI can help brands generate, adapt and optimize content at scale so that experiences are easier to understand and act on.

This includes creating clearer copy, producing more context-specific guidance, tailoring content to different audience needs and supporting omnichannel consistency. It can also help teams keep content more current and relevant across platforms. Done well, dynamic content generation improves one of the most basic but powerful parts of commerce: helping customers understand what they are buying, booking, changing or signing up for.

6. Better recovery when journeys break down

Not every commerce journey is linear. Customers abandon carts, encounter payment errors, lose confidence, switch channels or hit service obstacles halfway through. AI can help brands detect these breakdowns earlier and recover more intelligently. That might mean prompting the right help, surfacing the right next step, recognizing the customer across channels or tailoring recovery based on context.

The most advanced versions of this go beyond simple triggers. They combine service intelligence, journey analytics and customer data to help brands respond with more empathy and precision. In sectors such as travel, research shows that effective recovery can materially improve retention. Across industries, the same principle holds: when a brand handles disruption well, it can protect trust rather than erode it.

Useful AI depends on trust, transparency and strong data foundations

AI cannot fix broken commerce on its own. If the site is slow, the data is fragmented, the policies are confusing or the journey is structurally incomplete, AI will only amplify those weaknesses. That is why useful AI depends on stronger fundamentals: connected data, clear governance, modern platforms and experience design grounded in real customer needs.

Trust matters just as much. Consumers want personalization, but they also worry about data privacy and misuse. Brands need to be transparent about how data is used, give customers meaningful control and apply robust safeguards. AI should not feel intrusive, opaque or unpredictable. It should feel reliable, understandable and aligned with the customer’s interest.

This is also why human-centered design remains essential. The strongest AI experiences are not the loudest. They are the ones that fit naturally into the journey, solve a real problem and know when a human should step in.

A better standard for AI in commerce

For brands, the opportunity is clear. AI can help transform digital commerce when it is applied to the issues customers already care about most: finding the right thing faster, completing tasks more easily, getting help without delay, receiving relevant recommendations, navigating clearer content and recovering smoothly when something goes wrong.

That is how brands move beyond experimentation and hype. They focus on friction first. They connect data, service and experience. They deploy AI where it improves relevance, speed and clarity. And they build trust by making every enhancement feel genuinely useful.

In digital commerce, that is where AI stops being a novelty and starts becoming a competitive advantage.