News · AI Strategy & ROI

Palantir Raises 2026 Outlook as US Commercial Revenue Jumps 149%

Palantir's second-quarter revenue rose 93% to about $1.9 billion, US commercial sales grew 149% and full-year guidance went up again, a sign that enterprises are signing large, multi-year AI platform commitments.

By The AI Enterprise Magazine Team4 min readNews · Weekly briefing

Illustration of rising market bars over a network of enterprise data connections
Illustration of rising market bars over a network of enterprise data connections

Key takeaways

  • Fast growth at scale. Revenue rose 93% to $1.935 billion, with US commercial up 149% to $764 million.
  • Bigger commitments. US commercial contract value hit a record of about $2.1 billion, and 73 deals were worth $10 million or more.
  • Guidance up again. Palantir now expects 2026 revenue of $8.150 billion to $8.158 billion, about 82% growth.
  • What buyers want. CEO Alex Karp tied demand to AI sovereignty, customers keeping control of their own data and models.

Palantir's second-quarter revenue rose 93% from a year earlier to about $1.9 billion, and its US commercial business grew 149%, the company reported on August 3. It also raised its full-year outlook again. For enterprise technology leaders, the numbers are the clearest sign yet that large companies are moving from AI experiments to multi-million-dollar platform commitments, and that the platforms winning those deals are the ones that connect models to a company's own data and operations.

What did Palantir report for the second quarter?

Total revenue reached $1.935 billion for the quarter ended June 30, according to Let's Data Science, which summarized the company's earnings release and business update. US commercial revenue was $764 million, up 149% year over year and 28% from the first quarter. US government revenue was $809 million, up 90%.

Profitability kept pace. Adjusted operating income was about $1.2 billion, a 62% margin, and GAAP net income was about $1.1 billion, investingLive reported. Palantir's own "Rule of 40" score, which adds growth and margin, came in at 155%.

The forward indicators were just as strong. Total contract value signed in the quarter was about $3.4 billion, up 49%, and US commercial contract value hit a record of roughly $2.1 billion, up 153%. The company closed 220 deals worth at least $1 million, including 73 worth $10 million or more. Remaining deal value in US commercial stood at about $6.2 billion, up 124%.

How much did Palantir raise its 2026 guidance?

Palantir now expects 2026 revenue of $8.150 billion to $8.158 billion, roughly 82% growth, and US commercial revenue above $3.424 billion, at least 134% growth. TIKR's review of the earnings call described it as the company's largest guidance raise yet, 11 percentage points above the growth rate implied a quarter earlier. Third-quarter revenue guidance is $2.160 billion to $2.164 billion.

Net dollar retention, a measure of how much more existing customers spend over time, was 157%, according to TIKR. That matters because it suggests growth is coming from customers expanding their use, not only from new logos.

Why are enterprises buying Palantir's AI platform?

CEO Alex Karp called the quarter "otherworldly" and tied the results to demand for what he called AI sovereignty, investingLive reported. His argument is that customers do not want their data used to train other companies' models, and want AI that runs on their own data inside their own controls.

That pitch lines up with what AI Connect event speakers have been hearing from buyers. Aaron Delp, Global Head of AI Technical Marketing at Mistral AI, said during a AI Connect webinar on why enterprises should own their AI that customers with sovereignty and compliance concerns want to keep control of "the data, the weights and the keys." Different vendors, same buyer instinct.

The other half of Palantir's appeal is its ontology, a structured model of a company's business objects and how they relate. Enterprises have found that models alone do not know what an order, a part or a patient record means in their systems. Panelists in a AI Connect webinar on the context layer for enterprise AI described the same gap, arguing that metadata, semantics and memory decide whether AI answers can be trusted.

What should enterprise AI leaders take from the results?

First, the size of the deals. When dozens of customers sign eight-figure contracts in a single quarter, AI has moved into the core budget, and with it come the questions boards ask about any large platform: lock-in, exit costs and measurable return. Enterprises signing multi-year deals should negotiate for data portability and clear success metrics up front.

Second, the speed of US commercial growth versus government. For years Palantir was seen mainly as a defense and intelligence contractor. Commercial revenue is now close to matching government revenue, and Karp said he wants the whole business to grow as fast as US commercial over the next 18 months, according to TIKR.

Third, the results are a reminder that outcomes, not tools, close deals. "AI is a means to an end. It's not an end in itself," Mustafa Nisar, Senior Director, CX Data Science and Analytics at The Home Depot, said at COLLIDE 2025. Teams that tie each use case to a business result are better placed to justify contracts of this size.

What to watch next: whether Palantir's net dollar retention holds as contracts renew, and whether rivals selling semantic and context layers on top of existing data platforms start pricing against it in the same accounts.

Frequently asked questions

How much did Palantir's revenue grow in Q2 2026?

Revenue rose 93% year over year to $1.935 billion, with US commercial revenue up 149% to $764 million and US government revenue up 90% to $809 million.

What is Palantir's 2026 revenue guidance?

Palantir guided to full-year 2026 revenue of $8.150 billion to $8.158 billion and US commercial revenue above $3.424 billion.

Why are enterprises buying Palantir AIP?

Palantir says customers want AI that runs on their own data under their own control, and its ontology connects models to business operations.

Filed under: AI Strategy & ROI, Context, Semantics & RAG, AI Governance & Trust

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