AI layoffs is one of the main discussions and concerns in workforce management this week, as more companies publicly support AI cost-cutting over employee wellbeing.
With the technology increasingly influencing how organizations hire, there is still a crucial difference between redesigning work around proven capability and reducing headcount in anticipation of it.
Speaking with CX Today earlier this week, Lukas Alexander, VP of Customer Success at ChurnZero, explained why leaders need to become more aware of whether AI-led workforce protects, improves, or damages customer outcomes.
“Real genuine AI-driven efficiency means that teams can manage the same or more revenue with fewer resources and can maintain, or even enhance, the customer experience with the same or fewer resources,” he explained.
"The one thing that stayed the same … is that customers still need to see outcomes. I think that needs to be the measure.”
Whilst AI can remove routine work to create greater capacity, leaders cannot assume that the time saved automatically translates into better service or a more productive workforce.
This requires careful preplanning to decide where capacity will be reinvested, identify the human judgment that must remain in the loop, and measure outcomes alongside efficiency.
Microsoft’s Buyouts Put AI Workforce Efficiency Under the Microscope
Microsoft is reportedly offering buyouts to 60,000 employees as it seeks to reduce costs amid the growing use of AI, following on from its previous voluntary retirement scheme affecting 7% of its US workforce.
This offer is expected to involve some of its best-known divisions, including Xbox, Windows, and Copilot, with cybersecurity, datacenter, and marketing teams reportedly excluded.
This recent wave of technology-sector cuts is designed to enhance AI productivity; however, the lasting impact on operational efficiency remains mixed.
In numerous cases, vendors have overestimated the potential results of a mass layoff, with some rehiring only months afterward.
According to Forrester's 2027 predictions, CX staffing is expected to rise by 20% by the end of next year due to overcutting.
This gap in productivity is reportedly due in part to an organization's inability to effectively deploy AI tools, as only 45% of CX decision-makers' teams are actively using them.
As AI literacy grows significantly slowly alongside ever-increasing customer expectations, reducing capacity before measuring its effect on customer outcomes risks shifting work rather than eliminating it.
Teams should first distinguish the tasks that can genuinely be automated, and the work that still needs human oversight.
Before jumping to the wrong conclusion, companies need to decide whether the remaining workforce can sustain service levels without creating new bottlenecks or burnout.
Barclays Cuts Roles While Positioning AI as an Enabler, Not the Whole Strategy
Barclays’ similar approach to reducing its employee headcount highlights the difficult balance between AI-led productivity gains and customer commitments.
As the first major UK bank to make the AI-layoff plunge, this reduction is expected to remove 5,000 full-time roles by the end of this year, equivalent to 5% of its workforce.
This follows their earlier reductions at the start of the year, when Barclays removed 1,000 roles in an effort to reshape its banking strategy.