UBER Uber Technologies Inc. : Bullish and Bearish Analyst Opinions

Uber is cheap with strong earnings growth.

Gig workers are earning steady income and reinvesting it directly into UBER stock. This creates a "flywheel effect" where the underlying workforce supports the stock price with their own capital. Buying shares of Uber allows investors to profit from the continuous labor of gig workers. Macroeconomic slowdown affecting ride/delivery demand.

Uber is very cheap here.

Cramer calls Uber "a monopolist," says he "feel[s] the same way about DoorDash," and groups them with Airbnb as "brand-name companies" he "really like[s]" for long-term value. These companies have achieved dominant, platform-based market positions in their respective sectors (rideshare, food delivery, short-term rentals), creating durable competitive advantages. LONG for long-term investment based on sustainable market leadership and brand power. Increased regulatory scrutiny, heightened competition, or a severe consumer spending downturn.

Uber has the largest ride-hailing and delivery network, is forming capital-light partnerships with multiple autonomous vehicle (AV) players (Lucid, Rivian, Pony.AI), and is a cash flow machine. The stock is disliked due to fears of competition from Waymo. In AVs, the largest network will win. Uber's strategy of fostering a multi-OEM AV ecosystem positions it to aggregate supply and meet demand, unlike a scenario where one company (e.g., Waymo) owns all vehicles. Its cross-platform data (rides + delivery) and Uber One membership create a durable competitive moat. LONG because it is the best-positioned logistics platform for the AV future and is currently undervalued as the market misprices this strategic advantage. Waymo or another single player achieves overwhelming market share and bypasses Uber's platform entirely, making its network irrelevant.

The rise of AI-driven software platforms like Empower threatens to disrupt the traditional business models of Uber and Lyft.

Uber is positioned to win in the autonomous vehicle space by owning the network layer, as most AV partners will not want to run their own networks, allowing Uber to consolidate the market.

Cramer says Uber is "basically a value stock," trading at 23x earnings, down almost 25% from highs, with a "terrific buying opportunity." Robo-taxi competition worries are overblown; partnerships with autonomous driving companies (e.g., Nvidia) integrate into Uber's network, not direct competition. Attractive entry point as growth potential aligns with value valuation; Nvidia endorsement adds credibility. AI disruption fears persisting, slower adoption of robo-taxis, macroeconomic softness impacting ride-share.

The author is publicly reversing a long-held bullish thesis on Uber, signaling a fundamental deterioration in the stock's outlook.

Speaker owns "a lot" of UBER and believes it will break its downtrend. Details a series of recent autonomous vehicle partnerships (Zoox/Amazon, Nissan/Waabi, Nvidia) that integrate potential competitors' fleets onto the Uber network. Uber's app becomes the aggregation platform for multiple autonomous vehicle providers (backed by major tech and auto companies), securing its position in the future market against Waymo and Tesla. The stock is exceptionally cheap (bottom quintile of S&P 500 P/E) while growth expectations (~36%) are triple the market median. The combination of strategic positioning for autonomy and deep value relative to growth makes the stock a compelling long. The recent partnership news is a catalyst for the stock to bottom and move higher. Execution risks on autonomous partnerships; competitive threat from Waymo/Google's direct integration into mapping apps remains potent.

Uber and Lyft shares rose 4.2% and 3.8% after announcing separate autonomous vehicle partnerships with NVIDIA. RBC Capital Markets noted the pacts reinforce their view that ride-hailing companies will have a "durable moat." The partnerships with a leading AI/chip company (NVIDIA) are seen as strengthening the companies' long-term technological positioning and platform utility. The market reaction and analyst commentary view the news as a clear positive for the business moat and future prospects, warranting a LONG view. Execution risk on autonomous vehicle rollouts and timelines; partnerships may not translate to near-term profitability.

ZOOX is on the way to create one of the best brands in the business in transportation... To have that experience on UBER will only magnify what it is bringing to the marketplace. Uber is successfully transitioning into a capital-light, neutral marketplace for autonomous vehicles, eliminating the need to fund its own expensive R&D. Conversely, Amazon's Zoox gets immediate, massive global distribution and high utilization rates for its capital-intensive robotaxi fleet without having to acquire customers from scratch. LONG. This partnership validates Uber's platform-as-a-service model for AVs and accelerates Amazon's monetization of its Zoox investment. Regulatory pushback on autonomous vehicles in major cities or high-profile safety incidents could stall the rollout.

We bring enormous distribution on a global basis... using the platform to expand their distribution. And I see the same thing with Zoox as well. Uber is executing a capital-light strategy by acting as the aggregator and distribution layer for autonomous vehicles. By partnering with AV manufacturers rather than building its own cars, Uber avoids massive R&D and manufacturing costs while cementing its app as the default consumer gateway for transportation, regardless of which company wins the AV hardware race. LONG UBER as it successfully transitions its marketplace to capture the high-margin economics of the autonomous vehicle revolution without the associated capital expenditures. AV deployment scales slower than expected, or a major competitor successfully builds a proprietary, closed-loop ride-hailing network that bypasses Uber entirely.

"Uber, lower 1.7%. Doordash down 1.4% at the closing bell. This is due to the idea that these companies actually have exposure to the cost for fuel, oil and the idea that all of this pressure could trickle out into the consumer." Gig economy platforms rely on independent contractors who bear the cost of fuel. When gas prices spike, these platforms must either implement fuel surcharges (destroying consumer demand) or watch driver supply plummet as the unit economics of driving become unprofitable. Avoid gig-economy delivery and ride-share platforms during periods of extreme energy price inflation. If the Middle East conflict resolves quickly and oil prices structurally collapse, these stocks will experience a rapid relief rally.

These companies actually have exposure to the costs for fuel oil and the idea that all this pressure could really trickle out into the consumer and make things more expensive. Gig-economy delivery and ride-hailing networks rely on drivers who bear the cost of fuel. As gas prices spike, platforms must implement surcharges to retain their driver supply. These higher costs are passed directly to consumers, which can destroy demand for highly discretionary services. SHORT. Spiking energy costs act as a double-edged sword, squeezing driver supply while simultaneously killing consumer demand through higher end-pricing. Oil prices could stabilize quickly, or these platforms may possess enough pricing power that consumers absorb the surcharges without reducing their order volume.

A caller asks about Uber dropping from high 80s. Cramer says, "I want you to stay in Uber." Cramer views the current volatility as short-term. He believes Uber is "taking over the world" and the stock is "way too cheap" relative to its dominance. LONG. Hold/Buy through the volatility. Regulatory crackdowns on gig economy labor.

An Uber job posting suggests the rideshare giant is stepping up efforts to test a subscription offering for more of its drivers around the world https://t.co/u1MNSeKqf7

"Regular everyday traveler... having to pay thousands to cab drivers... trying to organize how to get across the border." When air travel fails, ground transport pricing power skyrockets. Uber (which owns Careem, the dominant ride-hailing app in the Middle East) will see a surge in high-value, long-distance cross-border trips. Long Uber as a beneficiary of the modal shift from air to ground transport in the region. The revenue bump from this specific region may be negligible compared to Uber's global balance sheet.

These stocks are testing major historical accumulation zones or breaking out with strong momentum (specifically INTU). Solodin identifies these as having strong "network effects" and favorable technical setups (testing support with volume) while other sectors look overextended. Long on technical support tests. Broader S&P 500 correction.

The "Experience Economy" Pricing Power The speaker notes that during the Super Bowl, "flight prices surge, hotels double and triple their rates," and highlights the use of "Uber Black" as part of the luxury experience. The ability of travel and hospitality providers to pass on 200-300% price increases during marquee events signals robust consumer demand elasticity. While goods inflation may cool, the "Experience Economy" retains superior pricing power, benefiting premium mobility (Uber) and lodging/travel networks (Marriott, Hilton, Airlines). LONG. Consumer recession curbing discretionary spending on travel and leisure.

Uber's open network strategy for autonomous vehicles (TUN) will allow it to capture a dominant 25-50% market share, as it will be more profitable for AV operators to join Uber's network than to operate independently.

Joby Aviation and Uber are launching "Uber Air" in Dubai, expecting to carry passengers later this year. This marks a tangible commercialization milestone for eVTOLs (flying cars), moving from concept to revenue generation in a wealthy market. LONG on commercial execution and first-mover advantage. Regulatory delays or safety incidents.

Sharma argues that by 2028, AI agents will handle most consumer tasks, bypassing apps and intermediaries. He notes, "Intermediary sectors... have real risk." Business models based on "friction with a friendly face" (food delivery, ride-hailing, retail banking UIs) lose their moat when an AI agent executes the task directly for the consumer at the lowest price. This leads to margin compression and volume loss for aggregators. SHORT intermediaries and software companies that rely on seat-based pricing or app engagement. Regulatory intervention to tax AI or protect jobs could delay this transition; consumer adoption of agents may be slower than the 2-year timeline.

IBM stock tumbled 13% (worst day since 2000) after Anthropic announced "Claude Code," a tool that can modernize COBOL programming language (used by 90% of Fortune 500s) instantly. Payment and gig firms (Amex, DoorDash) also sold off sharply. IBM's "mainframe maintenance" moat relies on the scarcity of COBOL experts and the difficulty of migration. If AI can automate this migration, IBM's consulting revenue collapses. Similarly, AI agents threaten the business models of intermediaries like DoorDash and Uber. This is the "AI Scare Trade"—selling companies whose services are easily replicated by AI. SHORT. The market is repricing "legacy moats" that are actually vulnerabilities in an AI-native world. AI tools may prove less reliable in enterprise environments than advertised, leading to a reversion trade.

A new report posits a scenario where "Agentic AI" collapses barriers to entry for apps (threatening UBER/DASH) and supplants traditional software suites (threatening CRM/ADBE). IBM fell 13% on news that Anthropic's tools can modernize code, bypassing legacy maintenance. The market is pricing in a "terminal value risk" for legacy SaaS and gig-economy platforms. If AI agents can code a delivery app or manage customer data autonomously, the "seat-based" pricing power of these incumbents evaporates. SHORT / AVOID. The narrative has shifted from "AI benefits Tech" to "AI eats Software." Momentum is negative. The report is a hypothetical scenario for 2028; these companies may successfully integrate AI to defend moats (as argued later by Paul from Sagard).

Bought 22,400 shares @ $71.25

Mayor Mamdani explicitly stated: "If you can cook at home, please do so instead of ordering food to be delivered." This is a direct government plea for demand destruction. Combined with the "hazardous travel advisory" and unplowed side streets, delivery volume will collapse for 48-72 hours. Furthermore, the "wet and heavy" snow increases accident risk and liability for gig workers, potentially spiking insurance costs or triggering platform shutdowns in specific zones. SHORT. Immediate revenue hit for Q1 in a key dense market. Pre-storm stocking up might have boosted grocery delivery volume (offsetting restaurant delivery loss).

A security research report highlights risks AI poses to various sectors, causing a specific selloff. DoorDash, KKR, and Blackstone are down >8%. Uber, Mastercard, Visa, Capital One, and Apollo are down >3%. The report suggests AI efficiency could "replace white-collar jobs" and disrupt business models in gig economy, finance, and private equity. The market is pricing in "AI displacement risk" for these specific tickers. SHORT. The market is reacting violently to the narrative that AI is a deflationary force for these specific business models. The report may be hyperbolic; these companies are also adopters of AI which could eventually improve margins.

The "Catrini" thesis argues AI removes friction. Companies like DoorDash and Salesforce exist largely to manage friction or act as a middleman. If AI agents can navigate the web and order food/manage data directly, the "app layer" and "middleman fees" (interchange fees, platform fees) get compressed to zero. Avoid companies whose primary value is acting as a user interface or friction-reducer, as AI agents will bypass them for the cheapest underlying service. These companies successfully integrating AI to lower their own costs and retaining pricing power.

"The fewer passenger and commercial vehicles need to be assisted, the quicker we can respond to plows. Please do so instead of ordering food to be delivered." While bad weather typically spikes demand for food delivery, the city's explicit plea to stop ordering creates a "forced churn" event. NYC is a high-density, high-volume market for these platforms; government pressure to clear the roads effectively halts operations and revenue generation in this key geography for the duration of the storm. Short-term negative catalyst for gig-economy logistics stocks heavily exposed to urban centers. The disruption is transient; demand may simply shift to the following days (pent-up demand) rather than being destroyed entirely.