AI to wipe out 49% of customer service jobs by 2030

Forrester forecasts that 49% of current customer service jobs will be lost to AI by 2030. Its research suggests AI agents already handle most customer inquiries in many organisations.

The report describes a sharp change in how customer service teams are structured. Routine frontline work is expected to shrink while new roles emerge in AI oversight, analytics and performance management. Human staff are increasingly moving away from direct customer interaction and towards supervising, governing and refining automated systems.

Examples in the research suggest the transition is already well advanced in some operations. At Anthropic, AI is involved in 96% of customer inquiries, while at Heathrow Airport it resolves 90% of inquiries from travellers. At digital-first companies including Rocket Money and TeamSystem, AI handles between 68% and 80% of inquiries.

Those figures point to a faster rate of change than earlier rounds of automation linked to interactive voice response systems and chatbots. AI agents are now embedded in day-to-day service operations and are compressing traditional customer service roles more quickly.

Workforce shift

In Forrester's outlook, lower-tier customer service representatives will spend less time answering routine questions and more time supervising AI agents, handling exceptions and feeding back on system performance. More senior roles are expected to focus on technical, complex or relationship-led work, where automation is harder or more costly to apply.

The report also distinguishes between service models. High-volume contact centres, particularly in business-to-consumer settings, are expected to see the steepest reductions in frontline staff as AI resolves a larger share of incoming inquiries.

By contrast, lower-volume and more complex environments, often in business-to-business operations, are expected to face less severe displacement. In those settings, more cases still require judgement, collaboration and longer resolution times, leaving a larger role for human staff.

New roles

At the same time, customer service organisations are expected to need more staff in insight, analytics and AI governance. Those functions will become more important as automated systems generate more detailed data on service performance, cost and customer outcomes.

That could change how service departments are measured internally. Rather than focusing mainly on handling volumes and reducing costs, organisations may increasingly assess teams on how they improve customer outcomes and support broader commercial goals.

Kate Leggett, Vice President and Principal Analyst at Forrester, said the change should not be viewed simply as a headcount reduction exercise.

"AI agents are not just reducing costs in customer service - they are redefining what customer service work actually is. Over the next few years, we will see fewer people answering routine questions and many more people directing, coaching, and governing AI systems that interact with customers at scale. Leaders who treat this shift as a pure automation exercise will fall behind. The organizations that win will be those that redesign roles, invest aggressively in reskilling and continuous learning, and rethink how they measure success - turning customer service from a cost center into a source of customer value, loyalty, and revenue growth," Leggett said.

The findings add to a wider debate over how generative AI and automated agents will reshape white-collar work. In customer service, the effect is likely to be especially visible because much of the function is already standardised around repeatable tasks, measurable workflows and large volumes of interactions.

For employers, the report points to pressure to retrain staff whose work is closest to routine inquiry handling. For workers, it suggests technical fluency, data literacy and the ability to oversee automated systems may become more important than traditional call-handling skills.

Over the next two to five years, customer service organisations are likely to reduce traditional roles while adding more data-driven and technical positions focused on oversight, insights and customer value creation.