To really transform with AI, you have to remember that it’s not just about the technology.
Teams accomplishing the most aren’t just bolting on an AI solution, they’re redesigning around it. That means finding new ways of working and evolving their structure to create a system that can sustain and improve AI performance over time.
In The 2026 Customer Service Transformation Report, teams at every stage of maturity report their human agents taking on proactive work, such as training AI systems, or focusing on the most complex of queries and tasks. Job descriptions are changing too, with many organizations explicitly including new AI-related responsibilities.
We’re also seeing the rise of dedicated AI specialists. New roles like conversation analysts, knowledge managers, and AI operations leads are becoming standard, opening up new career paths for support workers.
This week, we’ll explore how support teams are being reshaped by AI and how to embrace the change.
This is part four 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.
AI is reorganizing core customer service operations
Support work used to be built around queue-level activity like ticket triage, routing, translations, and answering FAQs. But with AI tackling more and more interactions, roles are adapting to focus on optimization and performance.
According to our latest research, 45% of teams report updating job descriptions to include AI-related responsibilities, with 40% saying their human agents are now more focused on training AI systems. Another 27% report that human agents primarily handle the most complex escalations and edge cases, while a quarter say agents are doing more consultative and strategic work.
Even at the initial deployment stage, 16% of teams report spending less time handling support volume since implementing AI – and among teams who’ve reached maturity, that figure rises to 28%.
When Intercom’s Research, Analytics & Data Science (RAD) team interviewed 166 of our customers, similar themes emerged. Nearly all participants (≈95%) reported meaningful workflow changes, with manual processes being handled by AI, and humans focusing more on monitoring or fine-tuning AI outputs. Eighty-three percent of participants also reported seeing their team’s roles and responsibilities change to become more strategic and supervisory in nature.
As AI for customer service grows, new roles are emerging
It’s not just the work that’s changing, teams are also adjusting their structure to make the most of AI. This may look like reallocating existing staff to AI-focused roles or hiring for new skillsets entirely. Many of the most common job titles didn’t even exist two years ago.
Within our own team, we’ve added a range of AI-focused roles. Here’s a closer look at two of them:
Our Senior AI Knowledge Manager, Beth-Ann Sher, came from our existing team and transitioned from the role of help center manager. Like many careers transformed by AI, her role has evolved from administrative to strategic. She used to concentrate on customer-facing, self-serve content, but now she thinks about how this content, and other sources, can be optimized to drive our AI Agent Fin’s performance. The time and effort spent pays dividends in resolution rate improvements. You can hear more about Beth-Ann’s role here.
Our Senior Conversation Designer, Fred Walton, was hired specifically for an AI-first function and focuses on seamless customer journeys with Fin. His role is focused on removing friction and making the handoffs between automation and human support smooth, always keeping customer satisfaction top of mind. You can learn more about him and his day-to-day work here.
Both of these roles reside in our new “AI support” team, overseen by a dedicated senior CS leader. This was part of a larger team restructure that ensures ownership and accountability for our AI performance.
And these changes aren’t just happening at Intercom. We’ve seen several of our customers move into new AI-focused roles within their company.
Take Robb Clarke from RB2B, for example. He went from Head of Technical Operations to Head of AI. With Fin, his focus moved from repetitive support questions to managing knowledge and improving the system behind it. This freed him up to look at opportunities for proactive improvement within the product, addressing issues before they even occur.
Or Eric Broulette from Bloomerang, a support leader who leaned into AI and ended up as the VP of Support and Education. Through his team’s use of Fin, they finally achieved breathing room to focus on what’s next. Support agents are now stepping into new roles, contributing to meaningful projects, and building skills that used to feel out of reach. Eric believes that the attributes he gained through implementing Fin, cross functional influence, strategic thinking, and a willingness to rethink how a support organization could operate, gave him the strong foundation to take on his new role of vice president.
AI isn’t just transforming what’s possible for support but also what’s possible for support agents and their leaders. As Eric says: “Do not wait to embrace AI. It will unlock more career growth for your teams than you can imagine.”
How to prepare your support team to adopt AI
It’s clear from these findings, introducing AI to your support team will eventually change every agents’ day-to-day work. For support leaders at the beginning of their adoption journey, it may seem daunting to launch an initiative that will have such far reaching impacts. But we believe that the most successful support teams will build an entirely new operating model with AI at its core.
When bringing AI to your team, it’s important to be transparent: what’s changing, why, and what success looks like. Discuss how AI performance can be measured and improved, empower your agents to participate in the process, and communicate how their responsibilities will evolve. Ensure your AI Agent is something the team is involved in building, not something that’s happening to them.
This was paramount to our own support team’s transition.
At Intercom, we:
- Reset expectations around the amount of time that the team would spend directly supporting customers versus helping to drive continuous improvement of Fin.
- Highlighted the value of comprehensive knowledge for Fin, and encouraged the team to identify content improvements to boost its ability to answer questions. To enhance this effort, we allocated dedicated “out of the inbox” time, ensuring all agents could participate.
- Kept metrics like resolution rate top of mind, giving us a concrete goal to build towards.
Work like you’ve never seen before
We’ve learned that scaling AI is as much about people as it is about technology.
As AI takes on more work, support roles become more proactive and strategic, even for teams at the beginning of the implementation journey. Existing agents see their responsibilities expand, new roles emerge, and overall team structure adapts to concentrate on and benefit AI performance. In the process, support careers are transformed.
Next week, we’ll look at how support has become a proving ground for AI adoption and is influencing organizations to push it into other parts of the business.
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