Guggenheim upgraded Datadog's rating from "Neutral" to "Buy" on Thursday, setting a $175 price target that implies roughly 50% upside from Wednesday's closing price of $116.50. Analyst Howard Ma asserted that market consensus significantly underestimates the company's backend architecture and expanding AI-native revenue base. The stock rose 2.45% in premarket trading.

Ma's core argument centers on two factors where the market appears to have over-adjusted. Guggenheim believes Datadog's backend architecture forms a deep moat against commoditization via large language models or OpenTelemetry, supporting a multi-product revenue stream that competitors would find difficult to replicate. More immediately, pending pressure from Datadog's largest customer, OpenAI—which has stated plans to leave the platform for observability—is progressing more slowly than market fears suggest. Guggenheim's channel checks indicate the transition timeline has been extended, giving the company room to grow contributions from its base of 650 AI-native customers, including what the firm believes is an eight-figure contract with Anthropic.

The divergence from market consensus is a standout aspect of the report. Guggenheim projects 2026 revenue growth of 27%, compared to the market consensus of 20%, and an operating margin of 24.5% versus the consensus estimate of 21%. AI-native customers excluding OpenAI are expected to grow 220% year-over-year, adding approximately $160 million in incremental revenue. The validity of these assumptions will face their first real test when Datadog reports first-quarter results, expected around May 5.