Windows 11 Surpasses 1 Billion Users, Cloud Adoption Drives AI Innovation
Windows 11 reached a significant milestone, surpassing 1 billion users during the recent holiday quarter, according to Microsoft CEO Satya Nadella. This achievement marks a faster adoption rate compared to Windows 10, which took nearly six years to reach the same number, according to The Verge.
The announcement came during Microsoft's fiscal Q2 2026 earnings call, where Nadella stated that Windows 11 usage was "up over 45 percent year-over-year." This growth underscores the continued relevance of the Windows operating system in a rapidly evolving technological landscape.
Meanwhile, enterprises are increasingly turning to cloud solutions and AI-driven automation to optimize their operations. Western Sugar, for example, moved from on-premise SAP ECC to SAP S4HANA Cloud Public Edition ten years ago. According to Richard Caluori, Director of Corporate Controlling at Western Sugar, the company was trying to escape "a trainwreck: a heavily customized ERP system so laden with custom ABAP code that it had become unupgradable." This early cloud adoption has positioned them to leverage new AI capabilities being rolled out by SAP across various business functions.
However, the rise of cloud adoption also brings challenges, particularly concerning cloud spending. According to Gartner, public cloud spending is projected to increase by 21.3% in 2026. Yet, Flexera's State of the Cloud report indicates that up to 32% of enterprise cloud spending is wasted on duplicated, non-functional, or outdated resources. To address this issue, companies like Adaptive6 are emerging to help enterprises reduce cloud waste.
The integration of AI also presents new security threats. MIT Technology Review reported on the increasing use of AI by hackers, citing the Gemini Calendar prompt-injection attack of 2026 and a state-sponsored hack in September 2025 that utilized Anthropic's Claude code. In the latter case, attackers reportedly used AI to automate 80 to 90% of the operation, including reconnaissance, exploit development, and data exfiltration. This highlights the need for robust security measures to protect against AI-driven cyberattacks.
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