andrew macdonald

Autonomy is improving daily and will eventually surpass human drivers in all use cases. However, the market will support multiple winners (4-5 in China already, growing to 8-10), not a single monopolist. AV companies have expensive fixed assets requiring high utilization, so they will partner with Uber's distribution network of 200M monthly users across 75 countries rather than rely solely on their own 1P apps.

The AV market will fragment with 4-10 global winners (per China precedent), not consolidate to one. Uber's 200M monthly users create a distribution moat that makes partnership economically rational for AV fleets needing utilization. However, AV adoption in low-labor-cost markets (India, Brazil) will take decades, meaning human-driven rides remain majority of trips globally for a long time.

AV landscape will support multiple winners (Waymo, Tesla, 4-5 in China, eventually 8-10 globally); no single player will dominate globally. Uber's 200M monthly active users create distribution moat — AV fleets need utilization, making partnership with Uber economically rational even for strong 1P players.

Uber blew through its annual AI budget in 4 months due to vertical usage growth. Tangible ROI exists in internal processes (capital allocation 15h→2h, forecasting 8h→2h, marketing QA 2w→2d) via dedicated AI-engineer/business pods. However, precise quantification is difficult because freed capacity gets refilled with higher-value work. Solution: merge compute and headcount budgets into combined pools allocated by trusted leaders based on marginal ROI.

Uber One outperforms price promotions because member cohorts increase engagement over time, consolidate mobility spend, adopt delivery (stealing share from DoorDash/Deliveroo), and reduce churn; IGB efficiency improves with cohort age creating widening moat.

Membership programs create compounding value: cohorts increase usage over time, cross-sell between mobility and delivery (Uber Eats vs DoorDash), reduce churn, and improve market share resilience. Unlike price promotions whose impact dissipates, membership efficiency improves with measurement horizon, making it the highest IGB/$ lever long-term.

Geopolitical barriers make it implausible for a US tech company to become the market leader in China (ride-hailing or otherwise). Uber's China exit at a 'silver medal' outcome (equity stake in Didi) was the best realistic result. Lack of WeChat access during competition was equivalent to operating in the US without email or phone numbers.

Concrete AI efficiency gains exist (pricing, forecasting, QA) but bottom-up ROI attribution fails due to time reinvestment; companies should merge compute/headcount budgets for flexible allocation and constrain headcount growth to force AI productivity capture.