Uber CEO Dara Khosrowshahi has defended the company’s AI investments, stating that artificial intelligence is delivering “hundreds of millions of dollars of benefit” to the ride-hailing and delivery giant, even as concerns mount about a potential AI bubble. Speaking on the “On with Kara Swisher” podcast released Thursday, Khosrowshahi acknowledged the debate around AI valuations and the massive spending on data centers, but emphasized that AI has created tremendous practical value for Uber’s operations.
The CEO described Uber as an “applied AI business,” explaining that the technology is being deployed across virtually every aspect of the company’s operations. This includes pricing optimization, payment processing, driver-customer matching, routing algorithms, identification systems, and customer service. Perhaps most impressively, Khosrowshahi revealed that roughly 80% to 90% of Uber’s developers now use AI tools in their daily work, representing a fundamental transformation in how the company builds and maintains its technology infrastructure.
One of the most significant operational improvements involves system monitoring and problem diagnosis. Previously, Uber needed scores of engineers on call to troubleshoot issues, spending “hours and hours” identifying problems. Now, AI agents constantly monitor all systems and help diagnose issues, with human engineers overseeing the AI’s work. This has dramatically reduced response times and improved system reliability.
Khosrowshahi also pushed back against the notion that AI-driven productivity gains should lead to workforce reductions. While other tech leaders might see 20-30% productivity improvements as justification for cutting 20-30% of their engineering staff, Uber is taking the opposite approach. “I just think they become superhumans,” he said, explaining that Uber is actually hiring more engineers because each one has become more valuable with AI augmentation.
The CEO also discussed Uber’s partnership with Waymo and other robotaxi companies, noting that driverless vehicles are proving popular with customers who appreciate the privacy. He predicted that once autonomous vehicles become proven revenue generators, Wall Street will embrace them as investments, with private equity and debt firms financing autonomous vehicle fleets similar to how they’re currently financing data centers and purchasing Nvidia chips. Khosrowshahi envisions Uber playing a role similar to Marriott in the hospitality industry—primarily managing and franchising rather than owning the assets.
Key Quotes
The latest AI models are ’enormously more effective’ than previous generations, and are producing ‘hundreds of millions of dollars of benefit to us.’
CEO Dara Khosrowshahi quantified AI’s financial impact on Uber, providing concrete evidence that AI investments are generating substantial returns despite concerns about an AI bubble.
We are not building the picks and shovels but we’re riding on top of that spend, absolutely.
Khosrowshahi explained Uber’s strategy of leveraging AI infrastructure built by others rather than developing foundational AI technology, positioning Uber as an AI application company rather than an AI platform company.
I just think they become superhumans. So we are actually hiring more engineers because every engineer got more valuable to me.
The CEO rejected the notion that AI productivity gains should lead to workforce reductions, instead arguing that AI-augmented engineers are more valuable and warrant expanding the team—a counterintuitive approach to AI adoption.
AI agents are now ‘constantly looking at all of our systems’ and helping to diagnose problems. And then the human can look over the shoulder of the AI agent.
Khosrowshahi described how AI has transformed Uber’s operations, replacing the need for scores of on-call engineers with AI-powered monitoring systems that work alongside human oversight.
Our Take
Khosrowshahi’s comments represent a significant data point in the ongoing debate about AI’s economic value. While much attention focuses on generative AI and consumer-facing applications, Uber’s success demonstrates that the most valuable AI applications may be operational and behind-the-scenes. The “hundreds of millions” in benefits come not from flashy chatbots but from optimizing recommendations, routing, and system monitoring—unglamorous but high-impact use cases.
The CEO’s hiring philosophy is particularly noteworthy. In an era where many tech companies are using AI as justification for layoffs, Uber’s approach of treating AI as a force multiplier rather than a replacement could prove more sustainable and competitive. This suggests that companies may bifurcate into those that use AI to cut costs versus those that use it to amplify capabilities—with potentially very different long-term outcomes. The autonomous vehicle predictions also hint at how AI will reshape not just technology but entire capital allocation patterns across industries.
Why This Matters
This statement from one of the world’s largest tech platforms provides crucial real-world validation of AI’s business value amid growing skepticism about AI investments. While prominent investors like Michael Burry warn of overspending and a potential bubble, Khosrowshahi’s concrete claims of “hundreds of millions of dollars” in benefits demonstrate that AI is delivering measurable returns for companies that implement it strategically.
Uber’s experience as an “applied AI” company offers a blueprint for how enterprises can harness AI for practical operational improvements rather than speculative moonshots. The fact that 80-90% of Uber’s developers now use AI tools signals a fundamental shift in software development practices that will likely spread across the tech industry.
Perhaps most significantly, Khosrowshahi’s commitment to hiring more engineers despite AI productivity gains challenges the prevailing narrative about AI-driven job displacement. This approach suggests that companies viewing AI as an augmentation tool rather than a replacement strategy may gain competitive advantages. The discussion of autonomous vehicles and Wall Street financing also previews how AI applications will reshape transportation infrastructure and investment patterns in the coming years.