Stop using AI as a gatekeeper in customer care

As AI becomes more embedded in customer care, one concern continues to surface among customers:

“Will I still be able to talk to a real person if I need to?”

 

Many brands are racing to automate customer care, but not every customer wants a bot‑only experience. The real worry consumers have, according to recent studies, is that AI will make human support harder to reach.

 

That’s why the future of the contact centre won’t be defined by AI replacing human agents, but something more nuanced: AI that gets customers to the right resolution – human or automated – on the first try.

 

Customers don’t reject AI – just AI that gets in their way

 

There’s no question that consumers are growing more comfortable with generative AI, generally speaking. Deloitte reports that consumer adoption of generative AI more than doubled in the space of a single year, with 38 per cent of consumers saying they’ve used the technology beyond experimentation.

 

Still, being comfortable using AI personally is very different from trusting a brand’s AI to guide you through a service problem. Only 41 per cent of consumers believe chatbots are more effective than humans at resolving issues, according to a Wakefield Research study commissioned by CSG. More than half (54 per cent) said that when they’re routed to a chatbot or automated system, it makes them feel more like “the company doesn’t care about them” than “the company is using a more efficient system” to solve their problem.

 

Companies can shift that sentiment. In that same study, consumers were asked to rank the top three factors that would make them more comfortable with AI support. The top-cited factor? The ability to transfer smoothly to a human when needed (61 per cent), which customers prized even more widely than getting the issue resolved in one attempt (58 per cent).

 

That tension creates the central challenge for contact centres today: customers are fine with AI as long as it doesn’t trap them in the wrong experience.

 

Automation may reduce simple contacts, but it doesn’t eliminate the need for nuanced or emotionally charged interactions (where human agents excel). Companies attempting to aggressively reduce headcount are already rethinking those plans. Gartner predicts that by 2027, half of the organisations expecting large workforce cuts in customer service will ultimately abandon those efforts.

 

Customers want speed and convenience, but they also want control. If AI misses the context or the complexity of their issue, they want to know a human is still there to solve it.

 

Design AI as a traffic controller instead of a gatekeeper

 

If you want AI to reduce effort without leaving customers stuck, the priorities shift quickly.

 

Start with the handoff. A useful AI system shouldn’t triage endlessly or force customers to repeat themselves. It should identify the issue, collect essential context and route the customer to the right place quickly (especially when the stakes rise).

 

Metrics like first contact resolution (FCR) help here. As Gartner found, each additional channel increases the likelihood they will churn. Customers who had a service issue with a brand were asked whether they would stay loyal to that brand or switch to a competitor. Among customers whose issue was resolved in a single interaction, 56 per cent said they’d stay loyal. But among customers whose issue wasn’t resolved in a single interaction, that loyalty figure fell to 36 per cent.

 

AI shouldn’t inflate your containment numbers while quietly increasing repeat contacts. When that happens, the customer feels the cost long before the operation does.

 

Case study: a win-win of AI and human support

 

A real‑world example shows how this works in practice. One of the world’s largest technology companies faced a familiar problem: too many support calls were landing in the wrong place. Its interactive voice response (IVR) system was misrouting 60 per cent of inbound calls, especially in the online store support flow.

 

To fix it, the company partnered with CSG to implement conversational AI and intent-based routing. The goal wasn’t to eliminate human support, but to make sure the contact centre supplied human support only when customers truly needed it, and that customers always got connected with the right agent group to solve their issues.

 

The AI solution used natural language processing to understand customer intent and route calls accordingly. If a customer’s issue could be resolved through self-service, the system guided them to the correct knowledge base resource. If not, it connected them to the right agent group the first time. CSG tuned the company’s own AI models, raising intent accuracy from 80 per cent to as high as 98 per cent.

 

The results were quick and significant:

• A 43 per cent reduction in calls to live agents
• A 42 per cent improvement in customer self-service
• A 34 per cent drop in agent transfers

Most importantly, the human option never went away. Human agents became more effective at helping customers, and it was easier to reach the right people when it was truly needed.

 

What contact centre leaders should do next

 

Designing AI that doesn’t hide your humans starts with a few practical shifts:

• Redefine success beyond containment: track first‑contact resolution and repeat‑contact rates, not just how many interactions stay in self‑service
• Design escalation paths first: make the human path obvious and low‑friction for high‑stakes or emotionally charged issues
• Treat AI as a traffic controller instead of a gatekeeper: use AI to understand intent, gather context and route to the right human or self‑service path quickly
• Continuously tune against real conversations: use call transcripts and chat logs to refine intents and spot where customers still feel “stuck” in automation

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If your contact centre feels as overwhelmed as your customers, you’re not alone. CSG’s 2026 State of the Customer Experience Report: Winning Loyalty in the Age of Overwhelm, goes deeper into the patterns behind this tension: when AI helps, when it hurts, and what actually earns loyalty back. It’s a practical read if you’re ready to cut the noise and design support that gets it right the first time. Download it here.

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Dan Hartman, Director of Product Management, CSG