AI

Why AI is failing retail customer service (and how to fix it)

Done right, agentic AI and automation can fundamentally change how retail CX operates. However, most retailers struggle to implement AI effectively.

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July 14, 2026 by David Karandish — Founder & CEO, Capacity

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In June 2025, Forrester reported that CX was declining. Retailers took notice, and pressure began to mount. Since then, Gartner reports that 91% of service leaders have been given imperatives by their C-suite to implement AI to improve efficiency, cut costs and elevate the overall customer experience.

Yet according to a recent Qualtrics survey, nearly 1 in 5 consumers still see no benefit from using AI for customer service.

Done right, agentic AI and automation can fundamentally change how retail CX operates: less burden on employees, faster resolution for customers and support that scales without adding headcount. However, most retailers struggle to implement AI effectively, often tackling the wrong problems or missing key moments when human intervention is necessary.

Customers are walking away with lingering concerns

With a brief internet search, it's easy to find stories of AI contact center failures: Confusing IVR and frustrating voice agent interactions. Chatbots that leave you in an automated loop, populating FAQ articles when you really need to talk with a human agent. Automated messages that leave customers feeling unseen and their issues unresolved.

Countless retailers have implemented AI to cut service centers, not solve problems, and customers are feeling the impact.

The 2026 Closure Index Report findings reveal that only 42% of consumers walk away from service interactions with a sense of closure. The rest leave with lingering concerns or unresolved problems that fester over time.

On an emotional level, 33% survey respondents feel relieved after an issue is addressed, and only 17% report feeling confident afterward. That lack of confidence uncovers a root issue: Brands are solving the wrong problems with AI customer service tools.

How retailers are solving the wrong problem with AI

Despite negative feedback about AI in customer service, customers aren't against it. One study found that over half of consumers actually prefer using AI agents when they want immediate help. What they hate is getting stuck in an interaction without a path to human support.

When retailers implement AI agents and automation too fast or without intention, they're more likely to leave customers feeling stuck. Say a customer who's already feeling irritated has a nuanced question about something missing in their order. In that moment, they don't want to get trapped in a chat. They want to speak with someone who has context, can assess the situation with judgment and can address how they're feeling.

In general, research uncovers what customers really want from service interactions:

1. Speed: 43% say fast resolution helps them feel closure, particularly for everyday or time-sensitive issues.
2. Clarity: More than half of customers (52%) say clear communication helps them feel closure. They're looking to understand what happened, what was fixed and what to expect.
3. Smooth escalation: 85% say the ability to move seamlessly from AI to a human when needed matters to them.

Successful deployment happens when automation helps deliver all three.

What successful implementation takes

AI agents perform best on repeatable, high-volume tasks. So if retailers start implementing AI with the more complex problems before automating Tier-1 tasks, they're more likely to struggle to deliver speed, clarity or a seamless AI-to-human handoff.

Retailers should identify the most frequent requests or questions, and automate those tasks that follow a clear, repeatable workflow. With basic process automation, contact centers can start reducing the redundant administrative work that eats up agent time and creates inefficiencies, like routing order status inquiries, fielding return requests or surfacing tracking information.

Only after that initial tier of tasks has been automated and shown successful ROI should retailers move into the more complex tasks: handling nuanced order disputes, managing post-purchase escalations or supporting customers mid-transaction when frustration is already running high.

Organizations also must understand the limits of AI. Customers still want the human touch, particularly in more tense, complex situations. AI has the potential to improve customer experiences and help internal teams do their best work, but finding the balance will take discipline, intention and a clear understanding of what customers really want.

Where AI can transform retail customer experiences

Retailers that build on that foundation start to see AI deliver across every part of the support experience:

Faster service: AI agents deployed across channels can instantly answer FAQs and resolve tickets for faster resolution. Companies like Chewy have seen their AI customer care tools drive measurable reductions in handle time and support costs, demonstrating that speed and quality aren't mutually exclusive.

Smoother experiences: Tools like real-time agent assist, knowledge management and AI-powered help desks give agents the right information at the right moment, so customers don't feel the friction of a handoff.

Less pressure (and higher CSAT): Retail AI agents automate repetitive work on behalf of your team. When time-consuming work is handled by AI agents, human agents are free to focus on interactions that actually require human judgment, delivering better-quality care regardless of the request.

Build for balance

Consumers have already decided what they want from AI in retail: speed on the simple stuff, a human when it counts and a handoff so smooth they barely notice the difference. Retailers that build their AI support to that standard, with intention and discipline, will see a more sustainable approach that delivers both a better customer and employee experience.

About David Karandish

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