HomeAI & Quantum ComputingMicrosoft's Gaping $627 Billion Backlog Can't Mask Wall Street's AI Anxiety

Microsoft’s Gaping $627 Billion Backlog Can’t Mask Wall Street’s AI Anxiety

Microsoft is chasing two contradictory realities at once. Its commercial contract backlog surged 99% to $627 billion in the March quarter — a measure of locked-in future demand that would be the envy of most enterprises — while the stock trades 20% below where it started the year. The disconnect between those numbers defines the company’s current predicament: investors aren’t questioning whether Azure or AI will grow, but whether Microsoft can make money on them fast enough to justify a $190 billion annual capex bill.

The scale of the investment is hard to overstate. In the fiscal third quarter ended March 31, 2026, Microsoft poured nearly $31 billion into property and equipment. Management plans to spend $190 billion for the full year. To keep those new data centers fed, the company has taken the unusual step of building its own power plant. Dubbed “Project Kilby,” the facility will rise in West Texas in partnership with Chevron, using natural gas from the Permian Basin. Once operational in 2028, it will deliver 2.67 gigawatts exclusively to a Microsoft data center, bypassing the regional grid. Cost estimates run around $7 billion. Chevron has until the end of 2026 to give final approval.

The electricity pact is a direct response to the voracious energy needs of artificial intelligence. Microsoft’s AI business has already reached an annual revenue run rate of over $37 billion, up 123% year-over-year. But that top-line surge comes with staggering upfront costs, driven partly by higher prices for graphics processors. Wall Street has grown increasingly impatient for those outlays to translate into bottom-line returns.

Should investors sell immediately? Or is it worth buying Microsoft?

The financials show a company still firing on all cylinders. Third-quarter revenue climbed 18% to $82.9 billion. Operating income rose 20% to $38.4 billion, and net income jumped 23% to $31.8 billion. The Intelligent Cloud segment, which includes Azure, generated $34.7 billion in revenue — a 30% increase. Azure alone expanded 40%. Yet none of that has been enough to lift the stock out of its technical rut. At €321.45, Microsoft shares sit roughly 9% below their 50-day moving average and nearly 17% below the 200-day line. The relative strength index stands at 33.2 — just above the oversold threshold of 30. That suggests sellers have driven the stock to levels that historically attract bargain hunters, but so far the dip-buyers have stayed on the sidelines.

Beyond the cloud and AI storyline, Microsoft faces several operational distractions. The Xbox division is undergoing a painful restructuring under the code name “Project Helix,” involving layoffs and new hardware. Meanwhile, a shareholder lawsuit filed in Seattle alleges the company misled investors about user numbers for its Copilot product. There have also been hiccups in datacenter capacity: failed negotiations with Oracle created a temporary server crunch that forced Microsoft to scramble for alternative supply. To hedge its AI bets, the company is exploring integration with Chinese firm DeepSeek, signaling that OpenAI will not remain its sole engine for in-house AI services. The logic is straightforward: diversifying model providers could help amortize the monstrous infrastructure costs faster.

This week’s Cloud & AI Frontier Week — a five-day digital event for Europe, the Middle East and Africa — offers a window into how Microsoft is trying to reassure both enterprise customers and investors. The sessions cover everything from scalable Azure AI deployments and GitHub Copilot integration to data sovereignty and confidential computing. The message is that artificial intelligence is no longer a demo; it is a repeatable deployment pattern. But until the market sees concrete evidence that the $190 billion capex cycle is generating adequate returns, the share price will remain hostage to that doubt — no matter how big the backlog gets.

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