Transformation in action: Raising the bar for customer experience

Efficiency was always AI's first promise for support teams. The more interesting story is what comes next.

Customer Service

Published
Feb 20, 2026

Transformation in action: Raising the bar for customer experience

Efficiency was always AI’s first promise for support teams. The more interesting story is what comes next.

[Intercom VP of Customer Support Declan Ivory]
Declan Ivory

8 min

Delivering a perfect customer experience has always been the goal for support teams, and now with AI, this is actually possible.

In The 2026 Customer Service Transformation Report, we found that all teams are experiencing early wins from AI, like improvements to their speed, efficiency, and ability to serve customers across languages and time zones. These wins are helping support teams gain capacity and the further they push the technology, the more they are able to deliver quality improvements.

This signals a shift in priorities. As AI proves it can handle more, teams can focus on the customer experience in ways they previously couldn’t.

This week, we’ll explore how deep AI implementation unlocks new ways to bring value to customers.

This is part three of our five-part deep dive into our new research: “The 2026 Customer Service Transformation Report.” We’ll be sharing all five editions on our blog and on LinkedIn.

If you’d like to get straight to the report, download it here.

From reactive to proactive: driving better customer experiences

Traditionally, support teams were stuck in a reactionary state. With a growing backlog, volume outpacing headcount, and complex queries tying up the most experienced team members, there was little time to think about ways to improve.

But this year, things are changing. According to our latest research, 58% of support teams view improving customer experience and satisfaction as their top priority for 2026. That number has more than doubled since the previous year, when just over a quarter (28%) of respondents cited it as a top priority.

As AI takes on more of the manual work, it opens up humans to focus on actively improving the support experience. In other words, when the AI is working, the measure of success moves to how well it’s working.

At Intercom, we’ve been watching this transformation first-hand. As our Senior Director of Human Support, Bobby Stapleton, said on a recent episode of The Ticket podcast, mature deployment of an AI Agent provides “breathing room” for support teams. While we used to be focused on deflection, we can now look for opportunities to deliver consistently excellent experiences. This might mean increasing access to support, minimizing friction on the way to a resolution, or anticipating needs before they arise.

In our own support team, we opened up support to trial customers, achieved faster first response rates, and provided consultative sessions to onboarding customers. All while absorbing a 300% increase in total demand, without expanding headcount. This was possible due to our deep integration of Fin.

Across the industry, a similar story is being told.

When teams initially deploy AI, only 9% say they can always meet customer expectations. That number triples as teams reach a mature level of deployment.

Even as customer expectations remain high, they are more likely to be met by teams that deeply integrate AI into their support operation, creating robust systems and ownership models around it.

Bridging great support across channels

Heading into 2026, our data shows that teams are planning to invest in omnichannel support experiences. This makes sense; to meet and exceed customers’ expectations, you need to be wherever they are. Teams hoping to use support as a differentiator must prioritize consistency, regardless of location.

Planned investment for 2026 is distributed nearly equally across chat, email, and social messaging (36% each), closely followed by phone/voice (31%).

This shift signals that teams have moved beyond asking “Which channel should we optimize?” to “How do we deliver consistent AI-powered experiences everywhere our customers are?”

The opportunity here is huge. Teams that crack omnichannel consistency have a chance to continue bridging the divide between what customers expect and what they can deliver. Every interaction can be an opportunity to exceed their expectations and build long-term trust.

Omnichannel in action

Our customer Clay is a great example of a team that’s cracked consistency across channels.

Support is one of their main growth drivers so as their customer base expanded and ticket volume increased, they needed to scale without compromising on quality.

What makes Clay’s support organization particularly interesting is their strong community focus. Much of their early support effort was concentrated in Slack, where they built close, transparent relationships with customers. However, this focus on a single channel became a point of friction as they grew. Customers wanted the flexibility to reach them via email and in-app chat and Clay needed a way to deliver the same high standard of support everywhere.

To bring a unified support experience across these channels, Clay deployed Fin.

Today, Fin is involved in 90% of all queries and handles half of Clay’s total volume, upwards of 7,000 queries a month. All the while, first response rates have significantly improved and Clay’s support team is able to provide proactive, high-impact work.

That includes identifying content gaps for the education and content marketing teams, helping customers before they even ask a question, and surfacing feature requests and recurring challenges to the product team.

Clay proves that when support is truly great it can become a competitive edge. With AI, teams can stop working around limitations, and focus on delivering a superior customer experience that makes a difference. That’s the kind of progress that’s exciting to see.

Building superior customer experience with an AI Agent

As you plan to scale your own AI Agent and build towards mature deployment, here are five principles to keep in mind to provide consistently excellent customer experience.

1. Treat customer experience like a product

Treating support as a product means designing, building, and managing your support experience with the same rigor and accountability you would apply to your core product.

Just like product teams:

• You define goals (faster onboarding, higher CSAT or CX Score, lower churn).

• You map flows (AI starts the conversation, human handovers, proactive nudges).

• You instrument the journey (track handoffs, drop-offs, success states).

• You run tests and ship improvements (tone tweaks, fallback paths, training updates).

• You own the outcomes (gather feedback, measure performance, use insights to continuously improve the system).

2. Lead with AI, back with humans

AI isn’t replacing the human touch. It’s redefining when, where, and how it’s most valuable.

In a scaled model, AI becomes the first responder: the default entry point for every conversation (and the end point for most of those conversations too). But it doesn’t work in isolation. The experience should be hybrid by design.

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