The new customer service career path

AI is reorganizing how support work gets done

Support work used to be built around queue-level activity: ticket triage, routing, translations, answering FAQs. With AI handling more interactions, time is opening up to focus on different work. Our research shows that 27% of teams say human reps now primarily handle complex escalations and edge cases, while 25% report reps doing more consultative and strategic work.

What this looks like in practice

Eric Broulette joined Bloomerang as a support leader and ended up as VP of Support and Education. The path there ran directly through AI.

When his team adopted Fin, they finally created space to stop firefighting and start thinking. Support reps stepped into new responsibilities, contributing to meaningful projects and building skills that had previously felt out of reach. Eric found himself developing capabilities he hadn’t anticipated, like cross-functional influence, strategic thinking, and a willingness to rethink how a support organization could operate. Those attributes, built through the process of implementing and improving AI, gave him the foundation for a VP role.

His advice to other support leaders: “Do not wait to embrace AI. It will unlock more career growth for your teams than you can imagine.”

A similar pattern played out for Robb Clarke at RB2B. He went from Head of Technical Operations to Head of AI. With AI handling the repetitive queries, his focus moved from fielding support volume to managing knowledge and improving the system behind it, which in turn freed him to look at upstream opportunities for proactive product improvement.

In both cases, the career moves happened as a direct consequence of putting AI first and rebuilding around it.

How to position your team for this evolution

The structural changes happening across the industry require deliberate investment. Here’s where to start.

Identify who on your team is ready to grow into AI-focused roles

Look at who naturally gravitates toward spotting patterns, improving processes, or thinking about content and knowledge. Those instincts map directly to the emerging roles, like knowledge manager, conversation analyst, and AI operations lead.

Create space to develop new capabilities

If your reps are spending 100% of their time in the queue, they have no room to develop the strategic and analytical skills the new roles require. Building in dedicated time – even a few hours a week – for people to work on knowledge improvements, analyze resolution trends, or review AI performance creates the conditions for growth.

Make career progression visible

If you’re asking people to take on new responsibilities, be explicit about where that leads. Map out what an AI operations or knowledge manager progression path looks like in your organization,, and how performance gets measured. Ambiguity here kills motivation; highlighting the opportunity is what makes this AI journey real and exciting.

Track the evolution, not just the output

Standard support metrics, like handle time, CSAT, and ticket volume, don’t capture the value of someone who spends their week improving the AI system. Build in ways to measure and recognize the strategic work, or it will get deprioritized when things get busy.

Add a standing item to your team reviews that surfaces system-level contributions, like content improvements, resolution rate gains from knowledge work, or customer experience improvements from conversation design changes.

Where to start

Pull up your current team structure and job descriptions. For each role, ask: what does this person spend most of their time on today, and how much of that could your Agent handle in six months? The difference between what they’re currently doing and where AI is heading is the opportunity – for them as individuals and for the team as a whole.

In most cases, the people you need are already on your team, they just need the space, the structure, and the recognition to step into these roles. Where gaps remain, you’ll know exactly what to hire for because you’ve mapped the work first.