<?xml encoding="utf-8" ?> Microsoft Corp. MSFT has reorganized its Azure cloud leadership and accelerated its custom AI silicon roadmap—scaling its in-house Maia chip to multi-gigawatt deployments by 2027—in a bid to sharpen its focus on artificial intelligence and tighten control over the infrastructure powering products like Copilot and OpenAI models.

The recognition expands Simform’s growing portfolio of Microsoft specializations and deepens its ability to support

Microsoft is reorganising the leadership of Azure and merging some units, The Information reports. Database chief Arun Ulag is taking on a bigger role.

Azure demand is outpacing Microsoft's ability to supply it, Copilot seats are surging, and the backlog just hit a record, yet the stock has barely moved in a year. Here is what a steady monthly commitment could realistically turn into by 2030 under three very different scenarios.

Microsoft (MSFT) is reshuffling the leadership of its Azure cloud computing business after a number of senior officers, including artificial intelligence head Eric Boyd, resigned

Microsoft ( MSFT -1.64%) just reported a key milestone. On its earnings call for the fourth quarter of its fiscal 2026 (which ended June 30), it told investors that its cloud platform, Azure, had surpassed $100 billion in annual revenue for the first time.

Microsoft is changing how it reports its finances to investors by splitting its businesses into two segments and disclosing quarterly revenue for its Azure cloud business for the first time. The changes are meant to reflect the ongoing impact of AI on Microsoft and how the company now operates.

Microsoft’s cloud business crossed a line it had never crossed before: Azure passed $100 billion in annual revenue for fiscal 2026. In the fiscal fourth quarter alone, Azure and other cloud services grew 43% (unchanged in constant currency) That’s the paradox.

The stock is within 2% of its record close. Is cloud growth in the mid-40s enough to send it past?

Microsoft is transforming Azure into a full-stack AI platform by combining custom chips, advanced data center infrastructure and AI development tools to give enterprises more flexibility, performance and control over their AI workloads.