Introduction to Agent Governance: building a Foundation of Trust and Control – Part 1

by Anna Bordioug, Evi Van der Velden, Melissa Ballesteros, Femke Cornelissen, Chhavi Dave, Priya Vardhini, Ijeoma Ochuba, Elaine He, Chiara Alina | Feb 22, 2026 | Copilot Agents, Microsoft 365 Copilot, Microsoft Copilot | 0 comments

AI agents are moving fast. It is predicted that there will be 1.3 billion AI agents by 2028!

In the Microsoft ecosystem, this shift is accelerating through platforms and tools such as Copilot Studio, Microsoft Foundry, and the Microsoft Agent Framework, where agents can be created not just by developers, but increasingly by business users through self-service experiences.

Imagine an AI that can automate a complex procurement process, manage an IT helpdesk ticket from start to finish, or generate and distribute weekly reports. This is the power of agentic AI.

But with great power comes great responsibility (and new risks). Without proper guardrails, these digital workers can create chaos: sprawl, data leaks, or unintended actions.

This blog series will give you a practical, risk-based framework to securely harness agentic AI. In part 1 we will introduce agent governance concepts as well as a risk-based governance framework.

What is Agent Governance?

Simply put, agent governance is the framework of policies, controls, and oversight that ensures AI agents operate safely, securely, and in alignment with your organizational goals.

It’s about treating AI agents not just as tools, but as accountable digital actors within your environment.

Think of it like onboarding a new, incredibly fast employee. You wouldn’t give them a badge and a laptop without defining their role, access permissions, who they report to, and what decisions they’re allowed to make.

At its core, agent governance is the set of policies, controls, and practices that define:

Who can create agents
What agents are allowed to do
What data they can access
How they are monitored, managed, and retired
Who is accountable for their behaviour

Governance ensures agents operate safely, transparently, and in alignment with business intent. It’s about enabling safe self-service, trusted automation, and scalable adoption.

Risk-Based Agent Governance Framework

Not all agents are made the same. Some will have access to particularly sensitive information or carry out sensitive activities, while others will not. To support secure adoption, agent governance needs to consider agent risk.

Figure: A sample matrix risk calculation framework.

A risk-based approach allows organizations to apply controls proportionate to the potential negative impact that a breach would have on an organization and its stakeholders. This will be influenced by what an agent does, who uses it, and the data it can access.

Agent Risk	Description & Examples	Governance Approach
High-Impact	Agents that make autonomous decisions, handle highly sensitive / business critical data (PII, financial), or perform irreversible and sensitive actions. Example: An agent that approves invoices or modifies customer data.	Maximum Control: Strict identity and access controls including regular access reviews, close monitoring of audit logs, and identity governance. Explicit decision boundaries enforced with human-in-the-loop requirements for critical steps.
Medium-Impact	Agents that handle complex tasks, often within a confined scope (e.g., a team or department) and/or interact with sensitive data. Example: An agent that drafts project summaries from the Finance team.	Managed Control: Defined identity and activity scope, regular lifecycle reviews, and monitored activity.
Low-Impact	Agents with narrow, well-defined tasks that do not access sensitive data. Example: A personal productivity agent that helps manage an individual’s calendar.	Essential Hygiene: Basic ownership and lifecycle tracking to prevent agent sprawl. Self-service creation allowed.

Table: A simple risk-based framework to tailor governance efforts.

Governance Controls Available in the Microsoft Stack

You don’t have to start from scratch. The Microsoft ecosystem already provides many capabilities that empower agentic AI governance, including:

Entra Agent Identity

Creating and managing agentic identities supports administrators in building a comprehensive agent inventory as well as enforcing identity security and governance controls.

Agent 365

Recently announced at Microsoft Ignite, Agent 365 is the control plane for agents. It provides key benefits such as a registry, access controls, visualization, interoperability, and security for agents.

Purview and Defender

Capabilities across Microsoft Purview and Defender help administrators protect sensitive data from unauthorized agent access, restrict agent activities, proactively monitor for Shadow AI, and gain visibility across agentic workflows.

Additional platform controls

Additional controls across Microsoft Foundry, Power Platform, Teams, and more help administrators define controls for governing and securing agents across the environment.

These controls are powerful, but only when used intentionally and consistently.

Why Is Agent Governance So Important?

Governance isn’t about slowing innovation. It’s the foundation that allows you to innovate fast and confidently. By putting controls in place, you empower your teams to build and use agents safely, knowing there are guardrails to protect the organization.

1. Preventing Agent Sprawl

Without governance, agents can multiply quickly:

Duplicate agents solving the same problem
Orphaned agents with no clear owner
Outdated agents still accessing data or systems

Over time, this can create operational noise and inefficiencies, security risks, and loss of end user trust in the platform.

2. Protecting Enterprise Data

Agents sit at the intersection of users, data, systems, and automation.

Poorly governed agents increase the risk of:

Unintended data exposure
Over-permissioned access
Shadow workflows bypassing controls

Agent governance is therefore critical for enterprise data security and compliance.

3. Enabling Trust and Accountability

When an agent produces an output or takes an action, stakeholders need clarity:

Who owns this agent?
What data did it use?
Was it operating within approved boundaries?

Clear governance creates confidence, both for users and for risk, security, and compliance teams.

4. Scaling Adoption Safely

Perhaps most importantly, governance enables scale. A well-designed agent governance framework allows safe self-service, where innovation can flourish within clear boundaries.