During its Q3 2026 earnings call, Uber revealed that despite widespread buzz around personal AI agents, virtually nobody is using them to book Uber rides. The company reported only four rides booked via AI agents during its busiest week of the year (Halloween week). The scale of usage remains negligible across its ride-hailing business.
In contrast, Uber Eats saw slightly more AI activity during the same period—but still tiny relative to overall orders. Out of roughly 320 million trips and food orders combined across Uber and Uber Eats that week, only about 500 food deliveries were requested through AI agents. In short, even among the most tech-savvy users, AI agent adoption in Uber’s ecosystem is just emerging.
Why the Slow Uptake?
Uber’s leadership acknowledged that booking a ride via the Uber app is already fast—averaging about 50 seconds—while reordering a favorite restaurant takes only 90 seconds. That narrow time window leaves little room for AI agents to deliver meaningful time savings over existing workflows. These frictionless processes may help explain why users aren’t flocking to automation for tasks they can already execute quickly themselves.
Still, the company remains optimistic about AI agents’ long-term potential. Uber’s CEO suggested that there are plenty of opportunities for these agents to generate additional demand and expand access to its services. He noted that around eight major AI assistants currently exist—and that number is likely to exceed ten soon. Uber has been in talks with many of them as it explores future integrations.
Broader Context in the AI Agent Space
The AI agent trend has been accelerating lately. New startups, alongside major players like OpenAI, Google, Anthropic, Meta, and SpaceXAI, are building agents that do more than just chat—they act. Notable entrants have already made headlines: one raised capital at a multibillion-dollar valuation last year, and another claimed millions of users in its app store debut. Still, adoption for transactional tasks (rides, food orders) seems lagging behind other use cases like shopping or research.
Other platforms reflect a similar pattern. DoorDash, for example, disclosed that just a small number of orders are being placed via AI agents, with most users sticking to the native app. That suggests this slow shift isn’t unique to Uber—it’s a behavior trend across platforms where convenience is already baked in.
Even so, Uber’s financial team believes AI agents will eventually become more embedded. While today’s numbers are low, the expectation is that as more assistants mature, integrations solidify, and user awareness increases, demand will grow. Uber sees the rise of agents as a potential growth lever, especially as consumers become more comfortable delegating tasks to AI.
Ultimately, the story here isn’t failure, but early-stage inertia. Users generally fall back on familiar, fast tools until agents offer clearly superior value. Uber’s numbers underscore both the excitement around intelligent automation—and the distance still to go before it’s commonplace.
