Palantir shares jumped 16% after the data analytics company reported stronger-than-expected second-quarter results, powered by rapidly accelerating demand from U.S. commercial customers adopting its artificial intelligence software.
The company’s quarterly revenue rose 93% year over year to $1.94 billion, while adjusted earnings reached $0.41 per share. U.S. commercial revenue increased 149% to $764 million, becoming one of the strongest growth drivers in Palantir’s business.
Chief Executive Officer Alex Karp described the quarter as “otherworldly” and argued that customers increasingly want AI systems that allow them to retain control over their data, models, and operational decisions rather than becoming dependent on the largest language-model developers.
Commercial AI Demand Accelerates
Palantir’s results showed that demand for enterprise AI tools is extending well beyond experimental projects.
The company closed 220 deals worth at least $1 million during the quarter, including 98 contracts valued at more than $5 million and 73 worth at least $10 million. Total contract value reached $3.37 billion, while U.S. commercial contract value jumped 153% to a record $2.13 billion.
Palantir’s Artificial Intelligence Platform allows companies to connect AI models with internal databases, workflows, security permissions, and operational systems. Rather than developing a competing foundation model, the company positions itself as the software layer through which businesses can safely deploy models from multiple providers.
That strategy appears to be resonating with customers seeking practical financial and operational returns from generative AI rather than simply purchasing access to additional computing tokens.
Sovereign AI Becomes a Selling Point
Management attributed much of the demand to what it calls AI sovereignty.
The concept centers on allowing organizations to choose which models they use while maintaining control over sensitive information, intellectual property, and operational decisions. Karp said customers do not want their competitive advantages to become training data for future third-party models.
His comments were also a direct challenge to major AI laboratories such as OpenAI and Anthropic. Karp said Palantir customers had declined to become “vassal states of the language labs,” arguing that enterprises increasingly prefer flexible software capable of running different AI models in controlled environments.
This approach is particularly attractive to governments, defense organizations, manufacturers, financial institutions, and healthcare companies that cannot freely transfer sensitive data into external AI platforms.
Government Revenue Remains Strong
Commercial customers produced the fastest growth, but Palantir’s government business also expanded sharply.
U.S. government revenue rose 90% year over year to $809 million, while total U.S. revenue climbed 115% to $1.57 billion. The figures demonstrate that Palantir continues to benefit from demand across both public- and private-sector customers.
The company generated $1.06 billion in GAAP net income, a 55% margin, while adjusted free cash flow reached a record $1.22 billion. Palantir ended the quarter with approximately $9.2 billion in cash, equivalents, and short-term U.S. Treasury securities.
Palantir Raises Its Outlook
Following the stronger-than-expected quarter, Palantir significantly raised its full-year forecast.
The company now expects 2026 revenue of between $8.15 billion and $8.158 billion, representing approximately 82% annual growth. U.S. commercial revenue is projected to exceed $3.42 billion, an increase of at least 134%, while adjusted free cash flow is expected to reach between $4.5 billion and $4.7 billion.
The raised guidance strengthened investor confidence that Palantir is converting enthusiasm around artificial intelligence into measurable revenue, profits, and cash flow.
While concerns remain about the stock’s valuation and competition from rapidly evolving AI platforms, the latest results suggest Palantir’s enterprise-focused strategy is gaining momentum as customers demand greater control over how artificial intelligence is deployed inside their organizations.
