Uber employees have taken AI adoption to a new level, building an internal chatbot modeled after CEO Dara Khosrowshahi that staff use to practice their pitches before presenting to the actual boss. The revelation, shared by Khosrowshahi himself, offers a glimpse into how deeply AI tools are embedding themselves in corporate culture at the ride-hailing giant. It's a quirky example of bottom-up AI innovation that shows employees aren't just using off-the-shelf tools but creating custom AI solutions to navigate workplace dynamics.
Uber employees have apparently decided that practicing presentations on colleagues isn't nerve-wracking enough. They've gone ahead and built an AI version of their CEO to grill them instead.
Dara Khosrowshahi revealed the unusual internal project during recent remarks, saying Uber's workforce has gone "all in on AI" to the point of creating a chatbot modeled after him. According to TechCrunch, employees now use this digital Dara to rehearse their pitches before facing the real thing.
The AI CEO apparently serves as a low-stakes testing ground where workers can refine their presentations, anticipate tough questions, and presumably avoid the sweaty palms that come with pitching directly to the C-suite. It's unclear exactly how the chatbot was trained, but it likely draws from Khosrowshahi's public statements, internal communications, and perhaps recordings of past meetings to mimic his communication style and decision-making patterns.
This isn't just a fun side project. It's a signal of how rapidly AI tools are moving from experimental tech to embedded workplace fixtures. While most companies are still figuring out how to deploy ChatGPT for email drafts, Uber employees are building bespoke AI systems tailored to their specific organizational needs.
The chatbot represents a fascinating shift in corporate AI adoption. Instead of top-down mandates to use certain AI platforms, this appears to be organic innovation bubbling up from engineering teams. Employees identified a pain point in the presentation process and solved it with the technology at their disposal. That kind of grassroots experimentation is exactly what tech leaders have been hoping for as they push AI integration across their organizations.
