Morgan Stanley reiterates Tesla stock Equalweight on trucking outlook

Morgan Stanley maintained an Equalweight rating on Tesla with a $400 price target, but raised its Network Services bull-case valuation by $20 per share to $840 on autonomous-trucking potential. The firm estimates Tesla could generate $17B in autonomous-trucking software revenue and roughly $7.5B in incremental EBIT by 2040 if it deploys 82,000 Semi trucks, although TSLA trades at a 338x earnings multiple and is viewed as overvalued by InvestingPro. Offsetting the long-term upside, NHTSA is investigating Tesla's Cybercab certification process, while analyst targets remain highly dispersed from GLJ Research's $24.86 Sell target to StoneX's $475 Buy target.

Analysis

The relevant valuation question is not whether autonomous freight is economically attractive, but whether TSLA can convert prototype capability into regulated, insured, utilization-dense fleet operations before incumbent ecosystems do. The proposed software economics imply unusually high take rates for a carrier market that is cyclical, fragmented, and highly price-sensitive; fleets will demand independently verified safety data, uptime guarantees, and liability allocation before accepting per-mile fees resembling a large share of driver-cost savings. This favors early economics accruing to freight operators and insurers with proprietary operating data rather than necessarily to the vehicle OEM.

Over the next 1-3 months, regulatory scrutiny of Tesla's autonomous certification process is the more tradable variable than a 2040 freight model. Any expansion of the investigation, recall-related remedy, or evidence that commercial deployment requires materially more remote supervision would impair the implied margin structure and expose a premium-multiple stock to narrative compression. Conversely, a clean regulatory outcome and disclosed fleet uptime/safety metrics would be the first credible evidence needed to underwrite the option value.

Second-order beneficiaries of autonomous trucking adoption are likely large carriers such as JBHT and KNX, which can amortize dispatch redesign, charging/maintenance infrastructure, and compliance investments across dense lanes; smaller owner-operators face capital and network disadvantages. Daimler Truck (DTG.DE) and PACCAR (PCAR) remain more direct competitive risks to Tesla because their dealer service networks, fleet relationships, and residual-value financing are central to commercial truck purchasing decisions. The consensus may be underestimating that autonomy can expand carrier margins while reducing OEM software bargaining power as fleets multi-source vehicles and autonomy stacks.

Key Decisions for Investors

• Maintain TSLA as a tactical neutral-to-underweight rather than chase long-dated freight optionality; use rallies unsupported by disclosed Semi deliveries, autonomous miles, intervention rates, and fleet-level uptime to add downside exposure over a 1-3 month horizon.
• For defined risk, buy TSLA 3-6 month put spreads around regulatory milestones rather than outright puts. The thesis is multiple compression if certification scrutiny broadens; exit if the investigation closes without remedy and Tesla reports commercially meaningful autonomous fleet KPIs.
• Watch-list pair for a 6-18 month autonomy rollout: long JBHT or KNX versus short TSLA in equal beta-adjusted dollars, but initiate only after a carrier discloses measurable driverless-lane utilization. The pair captures carrier operating leverage while reducing exposure to broad EV/AI sentiment.
• Do not underwrite Morgan Stanley's freight software contribution into base-case earnings until Tesla provides binding carrier contracts, commercial insurance terms, and audited safety data. A credible disclosure of these items would falsify the skeptical take-rate thesis and warrant covering TSLA downside.