Morgan Stanley raises the target price of Palantir to $233; optimistic about AI's business driving sustained revenue growth
The Block
1h ago
Ai Focus
Morgan Stanley raises the target price of Palantir from $205 to $233, maintaining a "hold and watch" rating. The bank believes that its AI business is growing strongly, with expanding demand from corporate and government customers, driving revenue growth to accelerate for the 13th consecutive quarter, and has raised its forecasts for revenue and profit margins in 2027.
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On November 3, Morgan Stanley raised its target price for Palantir Technologies ( PLTR ) from $205 to $233, while maintaining a "hold and watch" rating. The firm believes that the AI business of Palantir is experiencing strong growth momentum, with ongoing expansion in demand from both corporate and government customers, driving revenue growth to accelerate for the 13th consecutive quarter. In the third quarter, the company's revenue increased by 96% year-on-year, and its operating margin rose by nearly 11 percentage points to 61.7%, with the sum of growth rate and margin reaching 158%.

Morgan Stanley noted that the revenue from Morgan Stanley's US commercial business in the third quarter increased by 148% year-on-year, while the growth rate of revenue from its government business accelerated from 90% in the second quarter to 96%. At the same time, demand from sovereign AI is becoming a new driver of growth. Palantir allows customers to use their own operational data to retrain open-weight AI models, thereby improving model performance and reducing application costs while retaining control over the data and models, and thus expanding the scope of application for AI technology in enterprises and government agencies.

Based on strong business performance and the application prospects of AI, Morgan Stanley has significantly raised its revenue growth forecast for Palantir to 65% in 2027 from 45%, and increased its operating margin forecast from 61% to 63.5%. The bank believes that Palantir's competitive advantages in enterprise data integration and AI model deployment will continue to benefit from the widespread adoption of open-weight models.

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