The crisis that exposed the artificial intelligence (AI) supply chain also revealed which companies sit above it.

Since Iran closed the Strait of Hormuz on Feb. 28, the global helium market has lost access to roughly 30% of total output. Qatar’s Ras Laffan facility, the world’s largest helium production site, has been idle since early March. Moody’s confirmed in April what semiconductor engineers had already calculated: There is no viable substitute for ultra-high-purity helium at scale, and the gas is indispensable at multiple stages of chip manufacturing. The companies that build the physical chips are working against a six-month stockpile clock.

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For investors trying to buy into AI right now, the supply chain question has a clear answer. The companies that matter most are the ones whose products are pure software. Two reported earnings this week make the case for them.

Lines of code spill out of a vault.
Image source: Getty Images.

1. Datadog

Datadog (NASDAQ: DDOG) reported Q1 2026 results on May 7, and the stock surged roughly 30% in trading, the largest single-session move in the company’s history. Revenue hit $1 billion, up 32% year over year, crossing the billion-dollar quarterly threshold for the first time. Non-GAAP earnings per share (EPS) grew roughly 30% to $0.60. Free cash flow came in at $289 million. The company raised its full-year 2026 outlook.

But the number beneath the headline matters more than the headline itself. Datadog now has approximately 4,550 customers with annual recurring revenue of more than $100,000. That’s a cohort that represents the company’s most durable revenue base and one that grew meaningfully year over year. These are enterprises with AI and cloud infrastructure that generate logs, traces, and metrics at a scale that demands a dedicated observability platform.

Datadog doesn’t need the Strait of Hormuz. Its product is pure software. The product is a cloud-hosted observability platform that monitors AI workloads, infrastructure, and applications through a browser and an API. There is no physical manufacturing process, no semiconductor fabrication, and no industrial gas in its cost structure; when a customer deploys Datadog, the only thing that ships is code.

What changed in Q1 is that AI workloads, GPU clusters, LLM inference pipelines, and agentic workflows started showing up in Datadog’s billing in a material way. The company’s GPU monitoring product, launched this quarter, gives AI teams visibility into their fleets’ cost and performance, a capability that did not exist two years ago and that every serious AI deployment now needs. The more AI deployments that go into production, the larger Datadog’s addressable market becomes — regardless of whether the Strait of Hormuz reopens tomorrow.



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