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State of AI Customer Support in 2026
A data-backed perspective on what AI is doing for support teams today.
AI is becoming an integral part of everyday customer support operations. Some of its most popular use cases include triaging tickets, updating knowledge bases, and handling L1 queries.
But what’s less clear is how effective AI is at doing these tasks.
We surveyed 700+ support leaders across the US to get to the bottom of this. To examine whether AI in customer support is all hype or follows through on its promises.
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Some of the key insights uncovered in the report.
14%
of support leaders say AI has significantly improved resolution times.
48%
of support leaders say their teams are moderately confident using AI.
50%
of support leaders say AI has not significantly lowered cost per ticket.
61%
of support leaders remain cautious about AI representing their brand.
25%
of support leaders say AI has clearly reshaped their team structure.
What CX leaders say
“I hear from countless companies every week claiming their AI will solve all my problems. The majority of them are snake oil. They’re built on shaky foundations and don’t actually do what they promise.”
Jordan Hooker
Customer Support Manager at Axuall
“AI is a powerful enabler – but not a replacement – for human empathy in customer support. The most effective teams use AI to eliminate friction and accelerate service, while reserving the final mile for a human. That’s where connection, loyalty, and remarkable experiences are created.”
Dan Gingiss
CX Keynote Speaker & Author of Becoming The Experience Maker
“We talk about AI often, we share learnings, news articles, and ideas. The important part is being open, even when the conversations are difficult. While governance is important, AI is an exercise in change management so listening trumps any other strategy, unless that strategy is to spark innovation through showing potential and possibilities.”
Karen Lam
Customer Support Director, Top Hat
This report is for support leaders who are asking...
- Is AI improving resolution times in a meaningful way?
- Is AI significantly reducing costs, or just shifting effort around?
- Do support teams fully trust AI or is human oversight still required?
