• New concerns are emerging that advanced AI models from Anthropic and OpenAI could reduce the need for traditional software platforms like Datadog.
• Commentary around autonomous AI agents has intensified recently, raising questions about the long term role of observability tools and monitoring platforms.
• This shift in sentiment is drawing fresh attention to Datadog’s business model and how it might adapt as AI capabilities expand.

For Datadog, ticker NasdaqGS:DDOG, this debate comes at a time when the stock price sits at $106.73, with a 7 day return of a 16.7% decline and a 30 day return of a 22.2% decline. The shares are also down 20.2% year to date and 26.3% over the past year, even though the 3 year return is 28.0%. That mix of shorter term weakness and longer term gains is part of what is driving investors to reassess the risk profile here.

As AI agents evolve, a key question for you as an investor is whether they end up replacing, absorbing, or complementing what Datadog offers today. This article looks at how credible that replacement risk might be, what it could mean for Datadog’s role in software monitoring, and which factors may matter most for long term positioning.

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The latest concern is that Anthropic and OpenAI’s newest AI models could let autonomous agents handle more monitoring and remediation on their own, which some investors fear could reduce demand for traditional observability platforms like Datadog, New Relic, or Dynatrace. The sharp pullback in Datadog’s share price lines up with this sentiment shift, as the market reassesses how much of the company’s recurring revenue might be sensitive to customers experimenting with AI-first tooling instead of long-standing dashboards and alerting workflows.

How this fits the Datadog AI narrative

This AI replacement worry sits awkwardly alongside recent commentary that has cast Datadog as a clear AI beneficiary, with several analysts previously calling it a top pick tied to AI workloads and IT observability. Investors now have two competing storylines to weigh: earlier expectations that AI-native customers and products could support higher usage over time, and the newer view that the same AI progress from Anthropic and OpenAI could compress the role of monitoring platforms or prompt large users to rethink spend allocation.

Risks and rewards investors are weighing

• ⚠️ Risk that large AI users experiment with in-house or agent-driven monitoring, which could pressure Datadog’s usage-based revenue from some workloads.
• ⚠️ Risk that the broader software selloff and concerns about workload migration to AI agents keep valuation multiples under pressure for longer.
• 🎁 Reward if Datadog’s own AI-powered features and breadth across logs, metrics, and security remain central even as customers adopt Anthropic and OpenAI tools.
• 🎁 Reward if continued interest from analysts who still highlight Datadog as an AI-focused name supports investor confidence once the current narrative shock settles.

What to watch next

From here, the key things to watch are customer comments on earnings calls about how they are using Anthropic and OpenAI agents, any references to workload migrations away from Datadog, and whether management leans into AI agent support inside its own platform. If you want to see how different investors are framing these trade offs, check out the latest community narratives for Datadog through this collection of investor views and storylines.

This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.