AI customer service costs rise without workforce savings: Gartner
WASHINGTON, UNITED STATES — Companies rushing to deploy artificial intelligence (AI) in customer service may not see the labor cost reductions they expect, as rising technology expenses and operational risks offset potential savings, according to new projections from Gartner.
According to a report from CX Dive, more than half of customer service teams are expected to double their technology spending by 2028, yet those investments are unlikely to translate into significant headcount reductions, the research firm said.
Gartner warned that automation still cannot fully replace human agents without risking service disruptions and weaker customer experiences.
Rising tech spend fails to offset labor costs
The firm said organizations pursuing aggressive automation strategies could face unintended financial consequences, particularly if they reduce staffing too quickly in anticipation of AI-driven efficiencies.
“Automation can’t replace human agents without the risk of operational disruption and a worse customer experience,” Gartner said.
Beyond performance concerns, Gartner highlighted the financial risks tied to rapid restructuring. Companies that cut staff prematurely may ultimately incur higher costs if they need to rehire or rebuild critical service functions.
“Moving too quickly can actually increase costs in the short term — especially if you need to rehire or backfill critical roles,” Emily Potosky, senior director analyst at Gartner, said in an email.
“More importantly, premature cuts can undermine your ability to reorganize your function for long-term value creation and growth,” Potosky added.
Hidden costs behind AI adoption and infrastructure gaps
While AI is often positioned as a cost-cutting solution, Gartner noted that companies frequently underestimate the full expense of implementation.
These include licensing fees, system integration, training, usage costs, and the need for new specialized roles such as data analysts and knowledge management staff.
“Many of the leaders we talk to have substantial technical debt, alongside outdated knowledge and data management practices,” Potosky said.
“They will need to dedicate funding to modernizing their infrastructure, or fail to get positive ROI,” Potosky added.
The firm also warned that poor infrastructure and rushed automation efforts can result in declining service quality, brand damage, and potential legal or labor-related risks in regulated markets.
Offshore and nearshore models gain relevance amid AI cost pressures
Industry examples continue to highlight the risks of moving too quickly toward AI-only service models.
Swedish fintech firm Klarna previously scaled up AI-driven customer service in 2024 but later reversed parts of the strategy, reintroducing human agents to ensure customers still had access to live support.
Consumer sentiment also reflects skepticism about fully automated service environments.
Research cited by Gartner suggests nearly half of consumers expect AI to handle most customer interactions within the next decade, though expectations for human support remain for premium or high-touch services.
From an outsourcing industry perspective, the findings reinforce the growing relevance of offshore and nearshore customer service models as companies seek cost optimization without sacrificing human support.
Rather than relying on rapid domestic headcount cuts driven by AI assumptions, firms may increasingly blend automation with distributed human support teams across global delivery centers.
This hybrid approach allows organizations to balance cost efficiency, service quality, and scalability—positioning outsourcing providers as key enablers in the evolving AI-driven customer service landscape.
