Uber Technologies

Uber's second-quarter operating performance was in line with our expectations, with gross bookings narrowly beating management’s forecast by 2%. We view the third-quarter outlook as slightly soft, with decelerating top-line growth and margin expansion.

 Why it matters: While autonomous vehicles remain small relative to the total footprint of ride-hailing (less than 1%), the key Uber debate remains the terminal impact of this new technology: leverage gained by removing drivers versus leverage lost from buying AVs and/or relying on too few providers. Current results don’t answer this key question, but we like certain defensive steps Uber is taking. On AVs, Uber is making progress with multiple partners (essential to the bull thesis) and spearheading an AV lab’s data sharing efforts to nurture this multipartner ecosystem. The firm also acknowledged Waymo dependency risk, but we view Tesla AV scaling as a key risk.

Network-effect metrics, like total users and frequency (trips per user) remain strong, reinforcing Uber’s marketplace flywheel. Only about 30% of US gross bookings come from the top 20 cities, which provides some padding against AV encroachment in the near term.The bottom line: We maintain our narrow moat rating and $76 fair value estimate as we balance the strength of Uber’s key marketplace metrics against our view that AV companies are willing to bypass Uber to control the rider relationship. We see the shares as slightly undervalued post-earnings, as the market seems to be aggressively pricing in terminal value risks associated with autonomy, but we would wait for a better entry point to provide extra margin for error. We remain bullish on food delivery marketplaces. A larger pool of drone and sidewalk robot companies gives food delivery marketplaces greater bargaining power over economics, a sharp contrast to Waymo’s clear leadership in ride-hailing AVs. Given the relative business mixes, this creates a better setup for DoorDash than for Uber.

Our $76 per share fair value estimate represents an enterprise value of 2.6 times our 2026 revenue estimate. We project that Uber's revenue will grow 11% annually over the next five years, on average, consistent with our understanding of the nascent but maturing ride-hail market.

To build our revenue forecast, we developed a model that captures the dynamics of a fast-growing yet maturing technology while also factoring in the incremental adoption of autonomous vehicles, or AVs. We forecast gradually decreasing year-over-year growth in gross bookings, starting at 20% in 2026 and declining to 4% in 2035. We believe Uber’s role as the premier demand aggregator in ride-hailing and delivery positions it well amid this potential technological inflection point in the industry, but we also bake in the risk that AV companies could operate their own applications and compete directly with Uber in the long run.

Uber has diversified segments that contribute to revenue. In the mobility sector, we anticipate continued growth in underpenetrated international and low-population-density markets. In delivery, we believe we are in the early innings of Uber’s e-grocery delivery venture, and we like the diversification that this revenue stream brings. We expect consumers to gravitate to convenience as e-grocery catalog sizes continue to improve. Uber’s smallest segment, freight, is positioned well to benefit from the increasing digitization of logistics.

We expect revenue to grow faster than key cost-of-revenue components, such as car insurance, resulting in gross margin expansion. Insurance costs have been a significant headwind for the ride-hailing industry. As of May 2024, insurance premiums rose a staggering 23% year over year, according to the consumer price index for motor vehicle insurance. By March 2025, this increase was 7% year over year. We expect increases to continue moderating over the next few years, helping improve Uber’s margin profile. On research and development, Uber has pulled back from capital-intensive autonomous technology development. This has boosted profitability, but also raises the question of whether Uber gave up too early, as it now lacks some bargaining power when negotiating with Waymo and Tesla. In sales and marketing, Uber has seen a downward trend, which correlates with it achieving critical mass. Currently, brand awareness (a la “ordering an Uber” or “Ubering”) is high, so we expect sales and marketing expenses to decrease as a percentage of revenue.

The firm had been unprofitable until 2022. Uber achieved GAAP profitability in 2023, and we project the firm will remain profitable in 2026 and beyond. Uber has historically struggled with negative operating margins, but we expect its 2025 adjusted operating margin of 11% to expand to 16% by 2030.

Uber operates as a dynamic marketplace that we believe warrants a narrow Morningstar Economic Moat Rating, driven primarily by network effects. While rivals also benefit from network effects, none match Uber's scale, which gives Uber a cost advantage by spreading fixed costs across more trips. The firm also fosters unmatched engagement, which provides an intangible asset in the form of user data. This user data contributes to virtuous cycles in which more trips generate more data, more data improves application performance, and improved application performance drives more trips. The strength of Uber's network effect is the critical determinant of its ability to maintain returns above its cost of capital over time.

The network effect can be thought of loosely as supply informing demand and demand informing supply. Supply is drivers, and demand is riders or eaters. Ride-hailing marketplace companies like Uber incentivize drivers and couriers (supply-side) by creating a marketplace where they can earn wages. At the same time, the ride-hailing marketplaces provide an on-demand service for riders and eaters (demand-side). Combining supply and demand creates a network in which Uber acts as an aggregator.

The keys to evaluating the strength of a network include various measurements, such as user base growth (monthly active platform consumers, or MAPC), engagement trends (frequency or trips per MAPC), and monetization trends (revenue per trip).

On core user base growth, the market leaders Uber and DoorDash have matured and stabilized, while the laggard, Lyft, has been lower and more volatile. Uber has averaged 14% annual growth in monthly active platform consumers since the start of 2022, while Lyft has averaged a subpar 10% with swings from 7% to 16% over the same period. Importantly, Uber maintains a growth rate that is superior to Lyft’s despite its far larger size—indicating that consumers (demand-side) are more attracted to Uber’s marketplace network, which, in turn, attracts more drivers (supply-side).

Engagement and frequency trends, as measured by trips per MAPC, further quantify the strength of network effects. Uber’s consistently high engagement of 16-18 trips per MAPC exceeds DoorDash’s 12-15 and Lyft’s 8-9. This metric underscores Uber’s platform stickiness, suggesting a deeply embedded value proposition for users. Stable engagement suggests Uber has evolved from a discretionary service into a daily utility for many customers.

Lyft generates the highest revenue per ride, but this figure requires a nuanced lens. Lyft's revenue-per-trip metrics are highly volatile, suggesting it adjusts pricing quickly to preserve market share. On the other hand, Uber’s monetization is skewed downward because of its global presence and exposure to lower-income economies. Most importantly, Uber’s monetization is stable and growing while it simultaneously captures more market share. According to Uber, the company intentionally keeps monetization slightly lower than Lyft to strategically limit Lyft’s market share while maximizing Uber’s profitability.

In addition to the figures Uber and its peers report directly, we have evaluated data provided by New York City. NYC publishes granular monthly statistics on paid rides. Looking at more than 1 billion rides over multiple years demonstrates the network effects present on Uber’s platform. Uber is gaining market share, scaling more effectively than competitors and effectively charging more per mile without losing customers.

While much harder to quantify, we believe Uber enjoys indirect network effects in the form of intangible assets. The value of Uber’s data is increasing as rides accumulate, allowing the firm to improve its marketplace pricing algorithms and utilization rates. This is shown by Uber growing faster and pulling away from its competition as it scales.

Today, Uber is the premier demand aggregator and has the most leverage over both supply and demand. Autonomous vehicle companies like Waymo and Tesla recognize Uber’s profitability from aggregation and thus are incentivized to develop networks of their own. However, demand is not linear throughout the day, complicating the calculus for AV companies and reflecting Uber’s competitive position. Demand for ridehailing is highly concentrated around the 8:00 a.m. and 5:00 p.m. rush hours, which presents a hard-to-solve capital allocation issue for AV companies. Either AVs build too much capacity (poor asset utilization) or too little (potentially poor user experience on a nascent platform). Supply on Uber’s platform more naturally adjusts to peaks in demand. Effectively, Uber can optimize utilization while AVs cannot.

Importantly, the nonlinear demand challenges facing AV companies can become less severe as AV hardware becomes more economical. As AV hardware components standardize and AV manufacturers scale, economic losses from poor utilization decrease (though they are not eliminated). Partnering with Uber could help an AV company avoid the risks of over- or underinvestment, but we acknowledge the temptation of verticalization, as it allows the AV firm to capture more of the economics associated with ridesharing. Still, we believe Uber is well positioned as a scaled demand aggregator, and this scale should allow AV OEMs to focus on core competencies, such as manufacturing cars.

In total, nonlinear demand risks and the associated potential for over- or underproduction support our base case that partnerships and licensing fees between marketplace aggregators and AV companies are the most likely outcome for the majority of players, making it more likely than not that Uber's returns will exceed its cost of capital for at least the next 10 years.

Uber’s role as the premier ride-hailing and delivery demand aggregator positions it as the perfect partner for autonomous vehicle companies looking to scale AV fleets and achieve high utilization rates.

Strong growth in Uber's core user base reinforces its network effect, creating a virtuous cycle in which more riders on the platform encourage more drivers to join, and vice versa.

Uber’s large user base provides rich data to further improve supply/demand matching algorithms, enhancing its proprietary fleet management software and value proposition for AV companies.

AV companies have a superior cost structure because AV companies do not need to pay drivers. AV companies will develop exclusive applications and effectively cut Uber out of the entire market.

Uber’s value proposition to AV companies is fragile and concentrated on lower-margin fleet management services like charging and cleaning.

Ride-hailing is still a relatively new industry, which leaves plenty of room for increased regulation. The mandatory classification of gig workers as full-time employees could compress margins and hurt the company.