Microsoft faces AI execution test as spending surges

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Microsoft AI earnings test

Highlights

Microsoft's capital spending grows from 12 percent of revenue in 2022 to about 50 percent this year, raising concerns about AI product costs and profitability.
Competition intensifies as Anthropic and OpenAI challenge GitHub in AI coding tools, while rivals' offerings like Anthropic’s Cowork encroach on Microsoft’s business software ambitions.
Microsoft establishes a new business unit to deploy 6,000 engineers at customer sites for AI adoption support, mirroring similar moves by AWS, OpenAI, and Anthropic.

AI strategy shifts raise cost and growth concerns

As reported by Financial Times, Microsoft’s position in artificial intelligence looks less assured than it did two years ago, when its partnership with OpenAI was widely seen as giving it a leading edge over other Big Tech groups. Its shares are down 18 per cent over the past two years, even as the broader stock market rises by about a third during the AI boom.

Investors are also weighing pressure on the company’s software model as AI changes how applications are built and sold. Concerns centre on how much demand Microsoft will capture from AI-powered products, and how expensive those services will be to provide.

The most visible shift is in capital spending, which climbs from 12 per cent of revenue in 2022 to about 50 per cent this year. Copilot, the company’s workplace AI assistant, is slow to gain traction, while Microsoft’s move to build more of its own models beyond reliance on OpenAI raises further questions about cost and competitiveness.

Competition intensifies across business software markets

AI labs are also pushing into markets where Microsoft once appears to have an early lead. GitHub stands out in AI coding tools, but coding agents from Anthropic and OpenAI have since drawn more attention, while Anthropic’s Cowork targets routine office work that could overlap with Microsoft’s own ambitions.

Last month, Chief Executive Satya Nadella says AI applications differ fundamentally from traditional software because they can improve as they absorb workflows, domain knowledge and accumulated judgment inside companies. He argues businesses need to train internal AI models and build continuous learning loops, creating a new software layer that coordinates both models and workers to improve results.

That shift also makes implementation more complex. Last week, Microsoft says it creates an internal business division intended to place 6,000 engineers inside customer sites to support adoption, while Amazon Web Services announces plans for its own group of forward deployed engineers and OpenAI and Anthropic deepen alliances with private equity firms.

Nadella warns that companies which fail to train their own AI systems risk handing more value to a small number of general-purpose models. For Microsoft, that warning also carries a direct business risk, because if those broad AI models dominate, parts of its software franchise could be hollowed out even as Wall Street looks for stronger growth signals in earnings later this month.

In our earlier MSFT price analysis, we noted Microsoft shares were trading under key moving averages as investors weighed downside risks ahead of the company’s upcoming earnings report. The piece highlighted how fresh legal scrutiny tied to AI-related disclosures, along with the company’s push toward more in-house AI models for core Office products, was adding uncertainty and keeping sentiment cautious.

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