Wall Street Sees 50% Upside for Palantir if AI Pace Slows

D.A. Davidson raised its Palantir price target to $250, implying about 50% upside and citing demand for model control and orchestration if frontier AI development slows.

D.A. Davidson raised its Palantir price target to $250 from $200 and kept a Buy rating after the AIPCon 11 conference. The firm estimated roughly 50% upside and pointed to growing demand from customers for control over models and data.

Analyst Gil Luria said customers are choosing different models for different tasks and want control over their own data and infrastructure. Luria called Palantir a “control plane and orchestration layer” for enterprise AI and argued that role would matter if safety concerns or new rules slow frontier-model development.

Palantir reported second-quarter revenue of $1.94 billion, a 93% increase year over year. U.S. commercial revenue rose 149% to $764 million, and U.S. commercial total contract value increased 153% to $2.13 billion. The company raised its full-year growth outlook to about 82%.

Rosenblatt analyst John McPeake maintained a Buy rating and a $225 target, citing customer checks that pointed to a “strong pipeline of potential commercial customer conversions across multiple verticals.” Nvidia is deploying a Palantir-based sovereign AI stack across its supply chain and pairing Palantir software with Nvidia’s Nemotron models.

Palantir’s stock trades at about 82 times expected forward earnings. Michael Monaghan of Founders ETFs warned the company must keep “earning” its valuation by beating expectations. Other large technology firms and software vendors are building governance and orchestration tools and expanding into government and cybersecurity AI.

Analysts highlighted the difference between a slowdown in frontier-model development and enterprise adoption. If enterprises continue to deploy AI and require software to manage multiple models, companies that provide governance and orchestration services would remain relevant even if frontier-model training slows.

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