Uber employees are using an AI-generated clone of CEO Dara Khosrowshahi to rehearse for meetings with the executive, he revealed on a recent episode of The Diary of a CEO podcast hosted by Steven Bartlett. Khosrowshahi shared that one of his team members informed him that certain departments within the company had developed a “Dara AI” — a digital replica of the CEO — to help employees refine their presentations before meeting with him in person. “They basically make the presentation to the Dara AI as a prep for making a presentation to me,” he said. The AI clone helps employees test their messaging, adjust slide content, and refine their delivery. “They have Dara AI to tune their prep,” Khosrowshahi explained. While it’s unclear how widespread the practice is across Uber’s global workforce, the anecdote highlights a growing trend of employees leveraging AI for high-stakes workplace preparation. The use of a CEO’s digital twin raises broader questions about how far AI’s role will extend within corporate hierarchies. Khosrowshahi acknowledged the irony when Bartlett jokingly asked if employees might one day present the AI version of him to the board. The comment drew laughter from both men. Despite AI’s growing capabilities, Khosrowshahi stressed that current models still struggle with real-time learning and decision-making — core skills for top executives. “When the models can learn in real-time, that is the point at which I'm going to think that, yeah, we are all replaceable,” he said. Uber has long relied on AI to power its ride-hailing platform, optimize routing, and manage supply and demand. The company is also expanding into new AI-driven services through its AI Solutions division, which contracts independent workers to train AI models for external clients. For Uber’s technical teams, AI is already transforming workflows. Khosrowshahi noted that about 30% of the company’s engineers are “power users” of AI tools. He believes AI can boost individual productivity by up to 25%. “If AI makes my engineers 25% more efficient, I’d want to hire more engineers, because I want to go faster,” he said. But he also recognized the trade-offs: “I may not decide to add engineering headcount. At that point, instead of adding an engineer, I should add agents and buy some more GPUs from Nvidia.” The story underscores a pivotal moment in corporate AI adoption — where tools are not just streamlining operations but reshaping leadership, preparation, and even hiring decisions.