Goldman Sachs upgrades Palantir to Buy, betting on demand for private AI systems

Goldman Sachs analyst Gabriela Borges upgraded Palantir from Neutral to Buy on October 8, setting a $230 price target over 12 months. The target implied 18% upside, according to Investing.com’s account on Yahoo Finance. Her bet: governments and businesses seeking localized AI systems will create more demand for Palantir’s customer-specific software.

Shares rose 2.4% following the upgrade, The Daily Upside reported. Borges’s argument addresses two questions facing investors: how much of Palantir’s AI opportunity is already reflected in its stock price, and whether a business that puts engineers alongside customers can grow efficiently.

The demand behind the upgrade

Borges sees an opening in sovereign AI: bespoke, localized systems for governments and enterprises that prioritize privacy. Her thesis favors organizations applying AI to their own information, rather than relying only on broadly available tools. Industries with fewer technical specialists are a particularly promising market in her assessment.

Goldman expects the market for bespoke software to outgrow packaged software over the next one to three years. Borges argues the strongest returns will come from applications tied closely to a company’s proprietary data, workflows and decision rules—not generic software that is merely good enough across many businesses.

The opportunity is not necessarily replacing companies’ core business systems. Goldman’s case includes software that connects gaps between separate systems for finance, customer relationships and human resources. Palantir’s Ontology architecture maps raw data into real-world operational objects that people and AI agents can act on.

Engineers are part of the bet

Palantir’s forward-deployed engineers work at customer offices, helping build systems with the company’s tools. Borges identifies that approach as an advantage in meeting demand for custom AI. It gives the investment thesis a concrete delivery mechanism: engineers help adapt software to the customer’s operations.

The scaling concern is whether that hands-on work requires ever more people. Borges argues the model is more than hiring engineers: it depends on tight feedback between field teams and product development. She says Palantir has refined those feedback loops enough to automate them through AI forward-deployed engineers. That is her assessment, not a separately measured productivity result.

Goldman nevertheless sees an attractive entry point. Its valuation argument uses a different comparison: Palantir trades at a discount to high-growth peers when enterprise value is measured against free cash flow. The bullish call therefore combines expected demand growth with a favorable peer comparison, despite the stock’s much higher earnings multiple than the broader market.