Your AI steering committee’s 2026 checklist: Observability

2026-04-16 · Source: The Microsoft Cloud Blog · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cloud Computing & IT Infrastructure, Cybersecurity & Data Privacy · Depth: Intermediate, quick

Summary

Microsoft has updated its "Grow Your Business with AI You Can Trust" framework, introducing "Observability" as a critical new pillar for 2026 to address the bottleneck of control in deploying autonomous agentic AI systems. The framework helps organizations maintain velocity and control by providing line-of-sight into AI agents, their data interactions, and actions. It emphasizes that governing AI requires visibility, preventing "shadow AI" and mitigating risks like security vulnerabilities and data leakage. The guide outlines four foundational questions for AI steering committees regarding inventory, identity, access, and outcomes of agents, and details four technical capabilities for platform visibility: Registry, Agent analytics, Agent map, and Role-specific oversight. Accenture's experience is cited, where a centralized platform with observability reduced AI app build time by 50%.

Key takeaway

For AI Architects and MLOps Engineers deploying agentic AI systems, ensuring robust observability is paramount. Your steering committee must confirm that your AI platform supports comprehensive visibility capabilities like a central registry, agent analytics, and an agent map to prevent "shadow AI" and mitigate security and data leakage risks, thereby enabling secure and controlled scaling of AI initiatives.

Key insights

Observability is crucial for governing and scaling enterprise AI agents, preventing "shadow AI" and mitigating risks.

Principles

• You cannot govern what you cannot see.
• Centralized visibility is a prerequisite for scaling AI.

Method

The updated framework introduces Observability, focusing on a Registry, Agent analytics, Agent map, and Role-specific oversight to track AI assets, performance, connections, and provide tailored metrics.

In practice

• Track all AI assets in a central registry.
• Monitor agent performance, usage, and costs.
• Visualize agent-user-data connections.

Topics

• AI Observability
• AI Governance
• Autonomous Agents
• AI Steering Committees
• Trustworthy AI

Best for: CTO, AI Architect, MLOps Engineer, Director of AI/ML, VP of Engineering/Data, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by The Microsoft Cloud Blog.