Microsoft Agent 365: The control plane for AI agents
- •Microsoft debuts Agent 365 to centralize deployment and governance of autonomous AI agents across diverse platforms.
- •Next-gen databases including SQL Server 2025 launched to provide a unified data estate for AI-first enterprises.
- •In-country data processing expands to 15 nations to improve sovereign controls for Microsoft 365 Copilot interactions.
Microsoft is pivoting its ecosystem toward autonomous systems that move beyond simple conversational interfaces to execute complex workflows. At the heart of this strategy is the debut of Microsoft Agent 365. This platform serves as a sophisticated management layer—or control plane—that allows organizations to deploy, organize, and govern AI agents. Crucially, it supports agents built on Microsoft’s own platforms as well as those from open-source frameworks, providing a unified oversight mechanism as companies scale their automation and integrate intelligence into daily operations.
To support the heavy data requirements of these intelligent systems, Microsoft is overhauling its backend infrastructure. The announcement of SQL Server 2025 and Azure Horizon DB marks the arrival of a unified data estate designed specifically for modern workloads. These next-generation databases are optimized to handle the massive throughput and low-latency needs of agentic applications, ensuring that the underlying intelligence has immediate access to high-quality information. This integration is essential for creating an "autonomous enterprise" where data flows seamlessly between agents and record systems.
Furthermore, the expansion of sovereign controls for Microsoft 365 Copilot highlights a growing commitment to regional data privacy. By providing in-country data processing for 15 nations, Microsoft is enabling governments and regulated industries to adopt AI while maintaining strict jurisdictional control over their information. As global leaders gather at Davos 2026, the focus has also expanded to include sustainability, ensuring that the surge in computing power required for AI transformation aligns with long-term environmental goals through more efficient infrastructure and strategic resource management.