Palantir Technologies (PLTR.US), a leader in AI-powered data analytics, released its earnings report on Tuesday morning Beijing time, and two key facts emerged simultaneously: U.S. commercial revenue surpassed U.S. government revenue for the first time, proving that AI software is being monetized at scale on the enterprise side; however, the year-over-year growth rate of total value of new U.S. commercial contracts plunged from over 153% in the prior quarter to 11%, creating a sharp divide among institutional and retail investors over how far Palantir's next phase of AI application growth can be seen amid the AI agent frenzy.
That is why, despite both earnings and guidance beating Wall Street analyst consensus, the stock still fell as much as about 10% in U.S. pre-market trading. Regarding Palantir's latest earnings report and management's optimistic outlook, Morgan Stanley's latest research note's core judgment is that Palantir is a major beneficiary of enterprise "sovereign AI" and the spread of open-weight models, highlighting that third-quarter revenue growth accelerated for the 13th consecutive quarter, with adjusted operating margin reaching 61.7%; at the same time, customer growth and several order metrics slowed.
Morgan Stanley therefore took a seemingly contradictory but actually consistent action: significantly raising 2027 and 2028 revenue and earnings forecasts, lifting the target price from $205 to $233, while maintaining an "Equal-weight" rating — a relatively cautious, neutral-leaning stance — without upgrading to the most bullish "Overweight" rating. Based on a closing price of $178.34, $233 implies 30.65% potential upside. After surging 340% in 2025, Palantir's stock has accumulated a gain of more than 130% over the course of 2025, making it a "bull market legend of the AI application software sector," and some veteran Wall Street analysts, including those at Morgan Stanley, believe the stock still has room to rise. In October, Palantir's stock fell from $187.05 to $184.11, a monthly decline of about 1.57%, outperforming the Nasdaq 100 and the Philadelphia Semiconductor Index by approximately 5.08 and 13.79 percentage points, respectively. But from an intraday high of $212.94 on October 12 to the pre-earnings close of $178.34 on November 2, the stock had already pulled back about 16%, failing to continue an independent rally as the AI trade receded.
U.S. Commercial Revenue Surpasses Government Business for the First Time — Why Can't Nearly Doubled Revenue Quell Order Concerns?
Palantir's earnings data shows that third-quarter revenue grew from $1.181 billion a year earlier to $2.313 billion, up 96% year-over-year and 20% quarter-over-quarter, beating the consensus estimate of $2.18 billion; adjusted earnings per share came in at $0.44, above the consensus estimate of $0.41.
The strongest growth remained in the U.S.: commercial revenue reached $984 million, up 148% year-over-year and 29% quarter-over-quarter, surpassing U.S. government revenue of approximately $953 million for the first time; the latter grew 96% year-over-year, also higher than the 90% growth in the prior quarter. By contrast, international commercial and government revenue grew 21% and 31%, respectively, without the same explosive momentum seen in the U.S. market.
Profitability was also backed by cash: GAAP operating income was $1.085 billion, a 47% margin; adjusted operating income was $1.427 billion, a margin of about 62%. By the company's own measure, the "Rule of 40" score — revenue growth plus adjusted operating margin — reached 158%. Operating cash flow was $1.205 billion, and free cash flow after capital expenditures was approximately $1.197 billion; the company's adjusted free cash flow was $1.216 billion.
The "Rule of 40" is a rule of thumb for measuring whether a software company can balance growth and profitability. Under Palantir's methodology, adding revenue year-over-year growth to adjusted operating margin, a total of 40% or more is considered passing. Palantir's third-quarter revenue grew about 96% year-over-year, meaning revenue was nearly double the year-earlier level; adjusted operating margin was about 62%, meaning every $100 of revenue retained about $62 in adjusted operating profit. The two add up to about 158%, far above the 40% benchmark. The 158% here is a composite score, not a margin, nor a profit growth rate.
Guidance and management's business outlook were similarly strong. Fourth-quarter revenue is expected at $2.649 billion to $2.653 billion, with the midpoint about 7.8% above the LSEG-compiled analyst consensus of $2.46 billion; full-year revenue guidance was raised to $8.530 billion to $8.534 billion, implying growth rising from about 82% to 91%, with U.S. commercial revenue expected to exceed $3.559 billion, growing at least 143%, and full-year adjusted free cash flow expected at $4.8 billion to $5 billion. Morgan Stanley estimates that if fourth-quarter revenue beats the guidance midpoint by another 5%, year-over-year growth could approach 98%, but that is Morgan Stanley's scenario estimate, not a company commitment.
What sell-side and buy-side analysts are really debating is orders after revenue. Total company total contract value (TCV) of new signings this quarter was $2.918 billion, up only 6% year-over-year; U.S. commercial TCV was $1.463 billion, up only 11% year-over-year. Remaining performance obligations (RPO) at period end were about $4.9 billion, up 88% year-over-year but flat quarter-over-quarter. Morgan Stanley also noted that net new U.S. commercial customers fell from 38 to 33.
Management explained on the earnings call that several sovereign AI initial contracts worth tens of millions of dollars had shorter terms than usual; shorter terms inherently reduce the full-life contract value, and contracts with original terms of no more than 12 months are not included in the company's disclosed RPO. At the same time, net dollar retention rose from 157% to 165%, and U.S. commercial total contract value of new signings over the past 12 months still grew 62%.
Therefore, Morgan Stanley's analyst team emphasized that the sharp decline in single-quarter order growth cannot be directly interpreted as demand collapse; but the market needs to see this batch of short-term contracts renewed and expanded on schedule to confirm how much of today's revenue growth can be sustained.
From Model Capabilities to Customer AI Workflow Budgets: Why Did Morgan Stanley Raise Cash Flow Forecasts but Lower Valuation Multiples?
The key to Palantir benefiting from the agent wave is its ability to connect models to the processes that enterprises actually run. Traditional data warehouses can calculate which orders may be delayed; Palantir's Ontology goes further by linking orders, inventory, factories, and personnel permissions, enabling agents to propose allocation plans within authorized scope, trigger approvals, and test decisions with execution results. The "sovereign AI" that Morgan Stanley highlighted in the earnings report is also not limited to government procurement: enterprises can retain control over proprietary data and model weights, use AIP Evolve to post-train and evaluate open-weight models, and choose models with the right cost and performance for each task.
Two specific examples from the management call cited by Morgan Stanley show that L3Harris completed fine-tuning for a specific task in less than 48 hours, with initial test performance exceeding the frontier model it previously used and costs reduced by 95%; a global home appliance company started with a $1 million pilot and by the third quarter had expanded to a $15 million annual contract value, covering commercial, financial, and supply chain processes. The former explains why customers adopt, and the latter explains how Palantir generates more revenue from adoption.
This strong contract expansion capability is the main basis for Morgan Stanley's upward model revisions. The bank raised 2027 and 2028 revenue forecasts by 19% and 28%, respectively, to $14.08 billion and $21.14 billion, implying year-over-year growth of 65% and 50%; among these, U.S. commercial revenue forecasts were raised to $6.80 billion and $11.42 billion. Over the same period, adjusted operating margin was raised from previous estimates of 61.0% and 62.1% to 63.5% and 65.5%, adjusted earnings per share from $2.31 and $3.27 to $2.79 and $4.31, and free cash flow in the model rose to approximately $8.39 billion and $12.84 billion.
This also explains the stock's resilience relative to chip stocks: Palantir can sell more and larger-scale workflows to the same customers and already generates substantial cash flow, without needing to first build a new data center to have a chance at earning the next piece of software revenue. Morgan Stanley raised its target price but maintained "Equal-weight" because it is bullish on the growth opportunity brought by sovereign AI, but remains reserved about whether a large customer base can sustain the current pace of contract expansion over the long term. Morgan Stanley's research found that some large customers spending more than $5 million remain sensitive to price and total deployment costs. The top 20 customers generated average revenue of $146 million each over the past 12 months, while overall customer count growth slowed from 24% to 20%; the more growth depends on existing customers expanding purchases, the more it hinges on whether new use cases can repeatedly prove returns.
Morgan Stanley's $233 base target already assumes 37% revenue CAGR over the next five years, reaching $41.2 billion by 2031, with free cash flow of $27.5 billion and a margin of about 67%. On valuation, Morgan Stanley changed its previous "2030 free cash flow per share of $7.07, at 41 times" to "2031 free cash flow per share of $10.98, at 30 times," then discounted at a 13% weighted average cost of capital and added back $7.9 per share in net cash. The target price increase relies on higher cash flow forecasts, not on giving the stock a richer multiple — which also means Morgan Stanley's target price can still rise because it expects Palantir to earn more cash in the future, while maintaining a degree of caution about how quickly it can continue expanding purchases from existing customers. If new customers and per-customer spending expand faster, Morgan Stanley's bull case is $336; if deployment costs limit adoption, the bear case is only $91, representing 88.4% upside and 49.0% downside, respectively, from the base closing price.
Wall Street Is Deeply Divided: Why Can the Same Earnings Report Support Both $265 and $130?
After earnings, Citigroup maintained a "Buy" rating on Palantir and raised its target price from $250 to $265, implying significant upside of 48.6% over the next 12 months. Citigroup's analyst team focused more on the simultaneous strength in U.S. commercial and government businesses, believing that contract terms affected the comparability of order figures. UBS maintained "Buy" and Baird maintained "Outperform," both with a target price of $250, implying 40.2% upside; UBS noted that U.S. commercial revenue growth exceeded its estimated range, but flat RPO quarter-over-quarter was weaker than its quantitative model expected. Piper Sandler maintained "Overweight" and raised its target price from $231 to $235, implying 31.8% potential upside.
On the cautious side, Cantor Fitzgerald maintained "Neutral" and a $207 target price, implying 16.1% potential upside; RBC Capital Markets raised its target price sharply from $90 to $130 but still maintained "Underperform," implying a pessimistic downside of 27.1%. These ratings and target prices are enough to show that the real disagreement between Wall Street bulls and bears is not whether AI software has customers, but whether the pace of contract expansion among existing customers can last long enough to support today's valuation.
Therefore, the most telling signal next quarter will be whether the value of new U.S. commercial contracts can rebound, while net dollar retention and cash margins remain strong.
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