Going Leaner: Uber, PayPal Trim Workforce as AI Expansion Accelerates

Amid aggressive AI push, major tech companies are reducing their workforce. In the last one year or so, several companies including Oracle, Amazon, Meta and Microsoft have reduced their workforce. The latest to join this league is Uber. 

Uber CEO Dara Khosrowshahi in an internal email to employees (later published online) said the move was part of the restructuring. 

He wrote: “…I’m sure you’re asking, ‘Why, and why now?’—particularly since our business is performing so well. Over the last 5+ years, Uber has grown by orders of magnitude, with our top line nearly tripling. We’ve built new products, expanded into new businesses, reached more consumers and supported more earners, and become a much larger and stronger company. But that growth has also brought complexity: more layers, more coordination, more fragmented ownership, and in some cases structures that made sense when businesses were smaller but no longer serve us well at our current scale.”

“The changes we’re making today are designed to do two things: make Uber simpler and faster, and create more capacity to invest in our future. A leaner organization will mean clearer ownership, faster decisions, and more time spent building rather than coordinating. It will also generate savings that we intend to reinvest in growth, innovation, and the capabilities that will matter most over the coming years.”

According to reports, between 200 to 300 employees in India are likely to be affected by the new restructuring regime. 

Even as Khosrowshahi’s letter does not refer to AI, a recent Bloomberg report noted that Uber capped usage of AI after the company exhausted its annual budget for the same in nearly four months. Interestingly, Khosrowshahi had previously disclosed that the company’s 10% of codes were written by AI agents and that other departments like legal and marketing were also increasingly using AI. 

It’s not the first time that a company has opted for drastic job cuts admitting it had become unwieldy to further scale. 

Uber’s approach however seems similar to Jack Dorsey’s Block which earlier this year announced reducing the workforce by half. 

“…we’re reducing our organization by nearly half, from over 10,000 people to just under 6,000. that means over 4,000 of you are being asked to leave or entering into consultation. i’ll be straight about what’s happening, why, and what it means for everyone…” Dorsey had said in a post. 

Meanwhile, PayPal has reportedly laid off 600 employees in India. According to reports, the move impacts 10% of the workforce in the country. The company also laid off more than 150 employees in Ireland, reports add.

It appears the job cuts are unlikely to go away amid hyper AI deployment across industries. 

Even as companies are directing a lot of capital towards AI, it remains unclear whether such moves have actual impact in the long-run. 

A recent Gartner survey says that job reductions due to enterprises piloting or deploying autonomous business capabilities do not appear to translate into return on investment (ROI).

The survey found that workforce reduction rates were nearly equal among respondents reporting higher ROI from autonomous technologies and those experiencing only modest gains or negative outcomes.

Using technologies such as AI agents, intelligent automation, RPA, digital twins and tokenized assets, autonomous business will move organizations from simple augmentation and automation to true autonomy, where both machines and people have more autonomy. This does not mean humanless business; rather, it means human-amplified business, according to the research agency. 

“Many CEOs turn to layoffs to demonstrate quick AI returns; however, this disposition is misplaced,” Helen Poitevin, Distinguished VP Analyst at Gartner, had said. 

“Workforce reductions may create budget room, but they do not create return. Organizations that improve ROI are not those that eliminate the need for people, but those that amplify them by aggressively investing more in skills, roles and operating models that allow humans to guide and scale autonomous systems.”