Leigh Dunsford, a crypto commentator on X, said that Waymo faces challenges related to scaling, cost, and real-world ride-hailing fit, particularly for flexible curbside pickups across a city.
“I see this is in software startups everywhere,” said Dunsford. “Internally they are struggling to gain any significant traction and are burning cash. This works for another year or two but ultimately the customer also fails to monetise and deal with the ‘one size fits all’ and demands excessive changes and customisations that slowly strangle the provider. IMO Waymo likely has a scaling, cost and market fit problem. People will argue that they’ve completed X amount of rides and miles however, this doesn’t address the real use case of being picked up from the curb, home, bus stop, school or anywhere that people demand ride hailing from.”
Autonomous-vehicle-only ride-hailing fleets like Waymo’s depend on a fixed pool of centrally managed vehicles. This model is similar to traditional taxi systems, where supply cannot quickly increase when there is a surge in demand from commuters, event-goers, or late-night riders. Research on mixed fleets indicates that while autonomous vehicles (AVs) can reliably meet predictable base demand, human drivers entering and exiting the network dynamically help absorb sharp peaks. This reduces queues and wait-time volatility compared with AV-only operations. Such findings support concerns that an AV-only approach may struggle with real-world curbside pickups from homes, schools, or bus stops unless complemented by flexible human supply.
According to Uber’s analysis of surge pricing during major events, ride-hail demand can be highly volatile and requires a quick response from flexible human supply. A case study of a sold-out New York concert demonstrated that demand spiked to roughly four times normal levels after the show. When dynamic pricing was disabled, wait times and unfulfilled requests increased sharply; however, when enabled, higher prices attracted more drivers to the area, restoring service levels much faster. This illustrates how human-driver networks can scale supply within minutes—a capability that fixed-size AV fleets may struggle to match during sudden peaks.
Recent analyses of California Public Utilities Commission data suggest that Waymo’s robotaxis still spend a significant amount of time “deadheading”—driving without passengers while repositioning between trips—despite rapid growth in rides. Independent summaries report that close to half of total miles in some periods are driven empty. This contributes to congestion and parking pressure while generating no direct fare revenue. Scholars studying autonomous-mobility systems note that managing empty-vehicle miles is a core challenge for fixed AV fleets and have proposed restrictions or fees on zero-occupant cruising in dense urban areas.
Tekedra Nzinga Mawakana serves as co-chief executive officer of Waymo, Alphabet’s autonomous-driving subsidiary. She is responsible for overall company strategy with a focus on commercializing the Waymo Driver across ride-hailing and logistics applications. A graduate of Trinity Washington University and Columbia Law School, she previously held senior legal, policy, and government-relations roles at firms including AOL, Yahoo, eBay, and Startec before joining Waymo in 2017. She later served as chief operating officer and became co-CEO in 2021.
