Contrary to widespread forecasts, artificial intelligence has so far only modestly reduced customer service staffing. A Gartner survey, conducted in July and August 2026 among 275 customer service and support leaders, shows that only 21% of them reported that their company had reduced its human agent headcount due to AI.
- Only 21% of customer service leaders have cut human agent staff because of AI.
- Some companies that cut staff are already rehiring, and Gartner expects half of them to do so by 2027.
- Most leaders use AI to reorganize work, and they scale it up only after proving reliable results.
- Leaders should define the main goal of AI investments and build a capable team, not cut headcount quickly.
Customer service is among the functions consumers appreciate little, with endless wait times, incorrect answers, and unpleasant interactions. AI could, in theory, solve these problems and save companies money. Customers, however, remain reluctant. According to a Gartner survey in 2024, a majority (64%) of the 5,728 people surveyed in December 2023 said they prefer that companies not use AI in their customer service, with the main fear being that it would make accessing a human agent much more difficult.
Limited Reductions, Already Followed by Rehiring
Among companies that reduced their human agent headcount due to AI, the average decrease amounts to 16.7% of staff over the past 18 months. Some are already reversing their decisions: 7% of the leaders surveyed indicate that their company has rehired human staff after previous reductions, and 11% plan to do so over the next 18 months.
Kathy Ross and Emily Potosky, analysts in Gartner’s Customer Service and Support practice, explain that companies can fall into the trap of ‘cut fast, rehire later.’ According to Kathy Ross, this happens when reductions are based on the expected value of AI rather than proven results. If the technology fails to handle the volume or complexity of the anticipated work, service quality can suffer. Gartner predicts that half of the companies that reduced their customer service staff due to AI will make hires by 2027. Rebuilding this capacity, however, can prove costly, as it requires recruiting, onboarding, and training, while also recovering lost knowledge and experience.
Indirect Strategies and a Reorganization of Work
According to Emily Potosky, most strategies employed by leaders to resize their workforce are indirect and take time. Forty-five percent of them report a hiring freeze, 39% reassign human agents to other divisions, and only 20% resort to forced staff reductions. At the same time, 71% of leaders reassign human agents to other functions within customer service and support, and more than half have hired specialized staff to support AI-related initiatives.
Emily Potosky adds that leaders are primarily using AI to reorganize work and increase capacity, not to massively replace their staff. To decide if AI is ready to take over, leaders must verify that it consistently delivers the expected results at an acceptable cost. Organizations should start with targeted use cases, test performance in real-world conditions, and only scale up when results are reliable.
Kathy Ross finally recommends defining the primary goal of AI investments, whether it’s reducing costs, maintaining revenue, boosting loyalty, or supporting growth. The goal, she says, should be to build a team capable of achieving the desired business outcomes, not to reduce headcount as quickly as possible.
