Waymo’s skyrocketing ridership in one chart

Waymo is now providing 500,000 paid robotaxi rides per week across 10 U.S. cities, a tenfold increase from ~50,000/week in May 2024. The company still reports a fleet of just over 3,000 vehicles (3,067 in Dec 2025 NHTSA data) and will debut a 6th‑generation self‑driving system on the Zeekr Ojai and Hyundai Ioniq 5, indicating higher utilization per vehicle. Growth is tempered by regulatory scrutiny (NHTSA/NTSB investigations into behavior around school buses and San Francisco concerns about stuck vehicles) and substantial competition from incumbents and other robotaxi entrants (Uber, Tesla, Pony.ai, WeRide, Motional, Zoox).

Analysis

Waymo’s scale advantage is now manifesting as meaningful per-vehicle operating leverage rather than just headline fleet size. Expect 20–40% improvement in revenue per mile over 12–18 months as denser routing, better dispatch algorithms, and geographic roll-up reduce deadhead miles and increase trip stacking; that magnitude would flip incremental margin on mobility services from negative to modestly positive even before pure profit-sharing with OEMs.

The competitive moat is increasingly data- and operations-driven: mapping density, edge-compute hardware validation, and maintenance ops are stickier than software alone. That favors Alphabet (GOOGL/GOOG) and incumbents who can amortize large fixed R&D and ops platforms; it creates a rising-cost cliff for smaller entrants that must replicate large-scale remote monitoring, safety review, and local operations teams.

Regulatory and municipal frictions are the principal short-term brake — probe outcomes, local permit restrictions, or mandated operator staffing levels can compress utilization and force re-engineering of dispatch and safety validation, turning assumed margin gains into multi-quarter setbacks. Key catalysts to watch over the next 3–18 months are measurable uptime improvements from new vehicle-gen deployments, city-level permit wins/losses, and any NHTSA/NTSB rulings that materially alter allowable operating envelopes; these will drive binary re-rating events rather than slow grinds.

Key Decisions for Investors

• Overweight GOOGL/GOOG (6–18 months): allocate incremental 1–2% NAV via a defined-risk call spread (buy 12-month 25–35% OTM call, sell a further OTM call) to capture convexity from faster-than-modeled monetization of robotaxi margins; target 25–40% upside if utilization keeps improving, max loss = premium (cap to 3–5% of trade notional).
• Pair trade — long GOOGL / short UBER (12–36 months): size 1–2% NAV net market-neutral exposure to secular margin shift from human drivers to autonomous fleets; expect asymmetric payoff if autonomous trips take share (target 20–30% gross on long leg vs 15–25% on short), tighten or unwind if Uber demonstrates accelerated autonomous rollout or regulatory relief for human drivers.
• Short TSLA robotaxi optimism (3–9 months): buy a 3–6 month 10–20% OTM put spread sized to 0.5–1% NAV to hedge against regulatory/safety headlines or execution misses on full-autonomy claims — payoff 3:1+ on headline-driven drawdowns while keeping defined limited loss.
• Speculative supplier play — WRD (6–18 months): small overweight 0.5–1% NAV via long calls (20–30% OTM) as a binary bet on supplier wins for next-gen vehicle installs and retrofit contracts; high volatility trade — cut if order cadence isn’t visible within 6 months or if OEM partnerships don’t publicly expand.