当支持团队成为公司级 AI 的蓝图

Building a great end-to-end customer experience with AI means going beyond support.

Every customer touchpoint, from the first sales conversation through to post-sales support and success, is an opportunity to get it right. Other teams are now turning to AI to transform how they show up for customers, and support, which led the way, has already written the blueprint.

In The 2026 Customer Service Transformation Report, it’s clear most businesses are thinking about what’s next, with more than half planning to scale AI to other departments. Interestingly, they often cite their early success with AI in support as motivation for the move. This makes support teams uniquely positioned to help lead the transition, a strategic role unimaginable just two years ago.

This week, we’ll look at how teams are introducing AI to other parts of the business, how to think about this expansion effort, and the new opportunities it creates for support leaders.

This is part five 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.

Support is just the beginning

Support was the first proving ground for AI, and our research suggests that businesses are now planning to expand its use to other areas based on the results it’s yielded so far. Fifty-two percent of respondents said that their organizations are actively planning to scale AI to other departments in 2026.

What will this look like? Our customers are already finding out. 

My favorite example is WHOOP, the fitness wearables company. They offer a premium product which makes their sales conversations more consultative than transactional. Customers want to know “Which membership is right for me?” or “How often do I need to charge my WHOOP?” According to Emily Shirley, Business Manager for Growth Product at WHOOP, if someone chatted with the inside sales team, they were twice as likely to convert, but they didn’t have enough reps to respond to incoming queries fast enough. Customers could wait more than 10 hours for a reply. 

With a big product launch on the line and an anticipated spike in prospective customer conversations, their three-person team needed help. So they deployed Fin to the “Join” page, the final step before purchase. 

With Fin resolving 84% of inbound questions, the sales team was able to focus on high-value leads. Together, they drove a 130% increase in attributable sales. 

The team is now exploring ways to expand Fin beyond FAQs, focusing on personalised conversation flows, multi-product recommendations, and richer data capture. As Emily says: “There are so many parts of the buyer journey where this applies. We’ve only scratched the surface.” 

Avoiding experience silos

It’s clear there’s a desire to push AI to other parts of the customer lifecycle, but there is a risk hidden in this expansion. If sales, customer success, and other departments all launch their own Agent, each operating in isolation, you can end up fragmenting the very thing our research says teams want to create. The second-most cited reason for pushing AI beyond support: desire for a unified customer experience.

Without shared context, each handoff becomes a source of friction where customers could receive inconsistent answers or be asked to repeat information. 

The opportunity (and the challenge) is to keep the customer at the center. Instead of department-specific Agents that operate independently, we must strive for cohesion. 

This is the future we’re building toward. We previously shared our vision of Fin becoming a “Customer Agent,” capable of handling the entire customer experience. This will mean Fin can function in many roles, supported by a memory that grows with the customer over time and deep knowledge of the business, creating a seamless experience for every interaction. 

A new frontier for customer service teams

Pushing AI into new parts of the business requires someone to own the process. And for many organizations, that’s the support team. Nearly a third of respondents (32%) confirmed their customer service teams are leading their business’ AI transformation strategy.

This presents a real opportunity for support teams to shape the future of customer experience. Instead of each function reinventing the wheel, support can act as a center of excellence, defining shared standards, guardrails, and operating practices that drive performance.

As our Senior Director of Human Support, Bobby Stapleton, puts it: “You already manage the most complex, high-volume customer interactions; you have rich data on customer needs and behavior; and you know how Agents perform in the real world. Those insights will be invaluable as AI scales across your business.”

We’re beginning to see this in our own team. As Fin has moved into sales, so too has our Senior Conversation Designer, Fred Walton. Fred has owned Fin’s service agent since we first rolled it out – learning what works, what doesn’t, and how to phase changes without breaking what’s already running. When it came to rolling out Fin Sales Agent, it made more sense to bring that expertise across than to start from scratch. Not least because a customer can start with a sales question and end up with a support one. Someone needed to make sure those two experiences worked as one.

As Agents like Fin expand their capabilities and move into new areas, we believe many customer service leaders will see their roles expand to include AI implementation across the customer journey. 

The blueprint is being written

Achieving perfect customer experience is AI’s biggest promise. But in order to get there, teams need to be smart about the solutions they deploy. A unified Customer Agent capable of handling the entire journey end-to-end will have a significant advantage, delivering consistent, context-aware experiences across every interaction. 

The Customer Agent future is being built right now, and it’s starting with the team pioneering AI transformation from the very beginning: support. For leaders in these organizations, this is a rare opportunity to shape how customer relationships will be built and maintained in the AI era.

Next week, we’ll look at Intercom’s own transformation and what an AI-first support organization looks like in practice.

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