Goldman Sachs Group, Inc. upgrades Palantir (PLTR.US) to "Buy," with a price target of $230, bullish on AI growth continuing through 2027.

Goldman Sachs Group, Inc. upgraded enterprise software company Palantir (PLTR.US) from "Neutral" to "Buy," citing its recent stock underperformance and improved valuation appeal. Goldman Sachs Group, Inc. analyst Gabriela Borges wrote in a note to clients: "We upgrade Palantir from Neutral to Buy with a 12-month price target of $230, implying approximately 18% upside." She noted that with Palantir currently at roughly $8 billion in revenue run-rate and approximately 100% growth, investors are primarily debating two questions: first, whether the best part of Palantir's AI opportunity has already been realized, or whether the market is deep enough to support another round of upward estimate revisions; second, how sustainable the company's FDE model is. Borges said the key takeaway from a recent series of industry conversations is that the stock is positioning for another phase of outperformance through 2027. She believes Palantir's total addressable market (TAM) may be undergoing "another step-function change," partly driven by sovereign AI, custom applications, and the company's new verticalization strategy. Additionally, Borges explained Palantir's FDE model. FDE typically refers to Forward Deployed Engineer, a model that requires a tight feedback loop between field teams and product teams to quickly understand customer needs and deploy solutions. She believes Palantir has refined this model to be "nearly perfect, and can even be automated through AI FDE." Market participants believe Goldman Sachs Group, Inc.'s upgrade comes at a time when Palantir has recently lagged and investors are divided over the high valuations and growth sustainability of AI concept stocks. Goldman Sachs Group, Inc.'s optimistic view implies that it believes enterprise AI demand, government contracts, and vertical industry expansion could still drive Palantir into a new growth cycle. However, the report also implies two key risks: whether the AI opportunity has been fully priced in, and whether the FDE model can continue to maintain efficiency as it scales.