Making AI Apps Enterprise-Ready with Microsoft Purview and Microsoft Foundry
Building AI apps is easy. Shipping them to production is not. Microsoft Foundry lets developers bring powerful AI apps and agents to production in days. But managing safety, security, and compliance for each one quickly becomes the real bottleneck. Every enterprise AI project hits the same wall: security reviews, data classification, audit trails, DLP policies, retention requirements. Teams spend months building custom logging pipelines and governance systems that never quite keep up with the app itself. There is a faster way. Enable Purview & Ship Faster! Microsoft Foundry now includes native integration with Microsoft Purview. When you enable it, every AI interaction in your subscription flows into the same enterprise data governance infrastructure that already protects your Microsoft 365 and Azure data estate. No SDK changes. No custom middleware. No separate audit system to maintain. Here is what you get: Visibility within 24 hours. Data Security Posture Management (DSPM) shows you total interactions, sensitive data detected in prompts and responses, user activity across AI apps, and insider risk scoring. This dashboard exists the moment you flip the toggle. Automatic data classification. The same classification engine that scans your Microsoft 365 tenant now scans AI interactions. Credit card numbers, health information, SSNs, and your custom sensitive information types are all detected automatically. Audit logs you do not have to build. Every AI interaction is logged in the Purview unified audit log. Timestamps, user identity, the AI app involved, files accessed, sensitivity labels applied. When legal needs six months of AI interactions for an investigation, the data is already there. DLP policy enforcement. Configure policies that block prompts containing sensitive information before they reach the model. This uses the same DLP framework you already know. eDiscovery, retention, and communication compliance. Search AI interactions alongside email and Teams messages. Set retention policies by selecting "Enterprise AI apps" as the location. Detect harmful or unauthorized content in prompts. How to Enable Prerequisite: You need the “Azure AI Account Owner” role assigned by your Subscription Owner. Open the Microsoft Foundry portal (make sure you are in the new portal) Select Operate from the top navigation Select Compliance in the left pane Select the Security posture tab Select the Azure Subscription Enable the toggle next to Microsoft Purview Repeat the above steps for other subscriptions By enabling this toggle, data exchanged within Foundry apps and agents' starts flowing to Purview immediately. Purview reports populate within 24 hours. What shows up in Purview? Purview Data Security Admins: Go to the Microsoft Purview portal, open DSPM, and follow the recommendation to setup “Secure interactions from enterprise AI apps” . Navigate to DSPM > Discover > Apps and Agents to review and monitor the Foundry apps built in your organization Navigate to DSPM > Activity Explorer to review the activity on a given agent/application What About Cost? Enabling the integration is free. Audit Standard is included for Foundry apps. You will only be charged for data security policies you setup for governing Foundry data. A Real-World Scenario: The Internal HR Assistant Consider a healthcare company building an internal AI agent for HR questions. The Old Way: The developer team spends six weeks building a custom logging solution to strip PII/PHI from prompts to meet HIPAA requirements. They have to manually demonstrate these logs to compliance before launch. The Foundry Way: The team enables the Purview toggle. Detection: Purview automatically flags if an employee pastes a patient ID into the chat. Retention: The team selects "Enterprise AI Apps" in their retention policy, ensuring all chats are kept for the required legal period. Outcome: The app ships on schedule because Compliance trusts the controls are inherited, not bolted on. Takeaway Microsoft Purview DSPM is a gamechanger for organizations looking to adopt AI responsibly. By integrating with Microsoft Foundry, it provides a comprehensive framework to discover, protect, and govern AI interactions ensuring compliance, reducing risk, and enabling secure innovation. We built this integration because teams kept spending months on compliance controls that already exist in Microsoft's stack. The toggle is there. The capabilities are real. Your security team already trusts Purview. Your compliance team already knows the tools. Enable it. Ship your agent. Let the infrastructure do what infrastructure does best: work in the background while you focus on what your application does. Additional Resources Documentation: Use Microsoft Purview to manage data security & compliance for Microsoft Foundry | Microsoft LearnRegistration Open: Community-Led Purview Lightning Talks
Get ready for an electrifying event! The Microsoft Security Community proudly presents Purview Lightning Talks; an action-packed series featuring your fellow Microsoft users, partners and passionate Microsoft Security community members of all sorts. Each 3-12 minute talk cuts straight to the chase, delivering expert insights, real-world use cases, and even a few game-changing tips and tricks. Don’t miss this opportunity to learn, connect, and be inspired! Secure your spot now for the big day: April 30th at 8am Redmond Time. See agenda details below and follow this blog post (sign in and click the "follow" heart in the upper right) to receive notifications. ❗UPDATE❗This event is expected to last around 2 hours and 15 minutes, due to the incredible number of community sessions that were submitted! 💖 Please see the timing table below broken out into sections of four talks each, and plan to arrive 10 minutes before the section that interests you, OR stay for the whole time! Speakers will be available in the chat to answer your questions; please ask your questions during their session. Spillover Q&A forum links will also be shared. The full session recording will be indexed and posted to Microsoft Security Community YouTube within 24 hours after the event. Bookmark this page or follow this blog post for updates! Agenda Legend ↩️ Data Lifecycle Management 🔐 Information Protection 🚫 Data Loss Prevention (DLP) 🦾 Data Security Posture Management (DSPM) for AI 🤖 Purview for AI 👁️ Insider Risk Management (IRM) 🔍 eDiscovery 📊 Governance 🗒️ Compliance Manager 🛡️ Data Security All times are listed in US Pacific/Redmond Time. Session lengths are rounded to the nearest minute. AGENDA Section 1 - approximately 8:00 am - 8:43 am ↩️ The Day Offboarding Exposed Infinite Retention — Nikki Chapple Length: 10 minutes | Topic: Data Lifecycle Management A routine Purview request led to an unexpected discovery: more than 9,000 orphaned OneDrives and thousands of inactive mailboxes still storing content long after employees had left. This talk explains how a retain-only policy created hidden retention debt and how Adaptive Scopes can help organisations separate active users from leavers to avoid similar pitfalls. 🔐 The Purview Label Engine: Automated Classification, Translation, and co-Documentation for Enterprise Tenants — Michael Kirst-Neshva Length: 12 minutes | Topic: Information Protection Global enterprises face the challenge of implementing uniform data protection standards across borders and languages. In this talk, I’ll present a framework that makes Microsoft Purview labels truly scalable. Discover how to roll out parent and child label logics automatically, manage priorities with a single click, and generate instant compliance documentation for every business unit. 🗒️ What's In My Compliance Manager Toolbox: A Cloud Security Architect's Perspective — Jerrad Dahlager Length: 8 minutes | Topic: Compliance Manager A practical walkthrough of how I use Compliance Manager across real client engagements to map controls, track improvement actions, and simplify multi-framework compliance. No theory, just what works in the field. 🛡️ Stop, Think, Protect: Data Security in Real Life with Purview — Oliver Sahlmann Length: 8 minutes | Topic: Data Security With simple labels and matching DLP policies, Purview offers a practical and accessible way to approach data security. This lightning talk uses a real-life traffic light concept to show how a low barrier to adoption can still drive meaningful protection and awareness. Section 2 - approximately 8:44 am - 9:15 am 🔐 Using Purview to prevent oversharing with AI services — Viktor Hedberg Length: 10 minutes | Topic: Information Protection In this day and age, AI is the big thing. However, Copilot has access to everything you can access, including potentially sensitive data. In this session we will look at how to prevent Copilot to access highly sensitive data, using Information Protection. 🦾 How I Helped My Customers Understand their AI Usage (and protect their sensitive data) — Bram de Jager Length: 5 minutes | Topic: Data Security Posture Management (DSPM) for AI As AI tools explode across the web, many organizations still have no idea what’s actually happening in the browser—where employees type prompts, paste sensitive data, or visit public AI sites outside corporate governance. In this lightning talk, I’ll share how I helped customers shine a light on this issue. We’ll explore how Purview Data Security Posture Management (DSPM) can reveal which AI tools employees use, what types of data they input, and where sensitive information may leak through prompts. I’ll walk through real customer scenario where we detected risky AI usage patterns—such as employees pasting confidential documents into public chatbots. 🔐 Four Labels Max for Daily Use: Which Ones & Why? — Romain Dalle Length: 8 minutes | Topic: Information Protection Sensitivity labels are one of the most critical parts of a Purview Risk and compliance deployment, if not the most critical, because it directly impacts how end-users and business units should allow or restrict themselves to share their business data, internally and externally, on a daily basis. Labels have not other options than being precise, meaningful, and balanced in terms of embedded data security. Setting the right taxonomy is core to success, and is everything but a one-time project. 🚫 Data-driven Endpoint DLP Solution with Advanced Hunting — Tatu Seppälä Length: 8 minutes | Topic: Data Loss Prevention (DLP) This lightning talk shows you how to use KQL queries in advanced hunting to easily build initial sensitive service domain groups for authorized and unauthorized domains based on your organization's usage patterns. The same approach can be used for numerous other similar solution refinement and design purposes. Section 3 - approximately 9:16 am - 9:46 am 🔐 The Purview Hack No One Talks About: Container Sensitivity Labels That Fix Oversharing Fast — Nikki Chapple Length: 10 minutes | Topic: Information Protection Most organizations tackle oversharing with manual fixes, but the fastest solution is often overlooked. In this lightning talk, I show how container sensitivity labels automatically apply the right sharing and collaboration controls, ensuring every new Group, Team or SharePoint site starts secure by default. 🔍 Does M365 Support eDiscovery? — Julian Kusenberg Length: 11 minutes | Topic: eDiscovery A myth-busting session that separates perception from reality when it comes to Microsoft 365 eDiscovery capabilities. 📊 Improving Discovery, Trust, and Reuse of Analytics with Purview Data Products — Craig Wyndowe Length: 5 minutes | Topic: Governance This talk shows how bringing Power BI and Fabric assets into Microsoft Purview Governance Domains and Data Products creates a single, trusted view of enterprise analytics. By connecting reports, semantic models, and underlying data with shared metadata, ownership, and business context, organizations can make existing assets easy to discover and safe to reuse. 🔐 Why You Should Create Your Own Sensitive Information Types (SITs) — Niels Jakobsen Length: 5 minutes | Topic: Information Protection An in depth analysis of why Microsoft SITs are not one-size-fits-all, and how to create your own using what Microsoft has already built for you. Section 4 - approximately 9:47 am-10:30 am 👁️ From Zero to First Signal: Insider Risk Management Prerequisites That Actually Matter — Sathish Veerapandian Length: 8 minutes | Topic: Insider Risk Management (IRM) A focused live demo showing the real world prerequisites required for Microsoft Purview Insider Risk Management to work effectively. This session highlights the critical Entra ID, Intune, Microsoft Defender for Endpoint, and Purview DLP configurations that must be in place before creating IRM policies. 🤖 Securing data in the age of AI — Júlio César Gonçalves Vasconcelos Length: 11 minutes | Topic: Purview for AI AI will transform business as we know it; but without proper governance, it can introduce serious risks. We’ll show you how Microsoft Purview enables organizations to accelerate AI adoption while maintaining security, compliance, and transparency. 🔍 Beyond eDiscovery - Purview DSI for Security Investigation — Susantha Silva Length: 11 minutes | Topic: eDiscovery Most people hear “Microsoft Purview” and immediately think compliance, eDiscovery, or legal holds. But this session highlights Data Security Investigations, showing how DSI lets you take a DLP alert or insider risk signal and turn it into a structured investigation. 🚫 Elevating Purview DLP with a real world use case — Victor Wingsing Length: 14 minutes | Topic: Data Loss Prevention (DLP) Learn how I hardened Microsoft Purview DLP beyond out of the box defaults—closing real world data loss gaps, tuning policies to actual user behavior, and turning noisy alerts into protection that really blocks exfiltration. - Quick Closing/ Resource SharingExtend data security to the network with Microsoft Purview and Microsoft Entra
Protection that keeps up with how data moves in the AI era Enterprise data used to be easier to contain. It lived in files, in apps you managed, within boundaries you controlled. Security teams could focus on endpoints and known systems, and that was often enough. That’s no longer the case. Today, data travels constantly between trusted endpoints and unmanaged web apps, SaaS apps, and most critically, generative AI tools over the network. Employees type and paste sensitive information into prompts, upload work-related files to external services or personal cloud storage, and interact with systems that sit entirely outside the traditional enterprise perimeter. AI has expanded the risk surface for potential enterprise data loss. That’s why Microsoft Purview and Microsoft Entra now integrate to extend data security to the network layer (available in public preview). Traditional data loss prevention (DLP) approaches lack real-time visibility and enforcement, flagging incidents after data has already left the organization. In other cases, vendors rely heavily on physical network appliances that are complex and expensive to deploy, or compute resources that can add significant latency. In the era of AI, that model breaks down quickly. Real-time data protection for how work happens today To adapt to how enterprise data moves in the AI era, we’re announcing the extension of data security to the network layer, powered by Microsoft Purview and Microsoft Entra, now in public preview. This integration brings together data context and identity-aware enforcement to help protect sensitive data in transit, in real time: Detect how sensitive data is shared to shadow AI tools, unmanaged SaaS apps, and personal cloud repositories Help block the sharing of sensitive data in real time based on identity, user activity, and data context, before data leakage occurs Unify investigation workflows by correlating identity, data, and insider risk signals across Purview, Entra, and Defender Prevent employees from sharing proprietary or sensitive organizational data to potentially risky locations such as consumer AI apps. By combining Purview data classification, DLP policies, and insider risk detection with identity-aware enforcement at the network layer through Entra, organizations can dynamically apply protections based on: The sensitivity of the data Who the user is How that user has interacted with sensitive data over time Together, Purview and Entra enable a modern approach to data protection that follows the data to prevent leakage instead of relying on at-rest controls alone. Not only that, but the same Purview classification and policies that you already leverage for the rest of your enterprise data can now be applied consistently across data in motion, at rest, and in use. Learn more in the detailed blog. See the capabilities in action here. Start your free trial of Purview Suite here.Microsoft Fabric Lakehouse sub-item metadata in Microsoft Purview
Working at the intersection of data security, engineering, and governance, the Microsoft Purview product team continually explores capabilities that reshape how organizations understand and manage their data estate. One such capability—the ability to scan and extract metadata from Microsoft Fabric Lakehouse—has generated genuine excitement and strong customer demand. We are pleased to announce the GA of Microsoft Fabric Lakehouse sub‑item metadata in Microsoft Purview. The Problem It Solves Anyone who has managed a growing data estate knows the pain: data sources and workspaces multiply, Lakehouse accumulate tables and files, and before long nobody has a clear, centralized picture of what data lives where, what it looks like, or how it flows. Data governance becomes a spreadsheet exercise. Audits become stressful. Trust in data erodes. Microsoft Purview directly addresses this by automatically scanning your Fabric tenant and bringing metadata into the Unified Catalog — without requiring your data teams to manually document anything. What Purview Actually Extracts Here is where it gets interesting from a product perspective. The integration distinguishes between two levels of metadata: Item-level metadata covers the top-level workspace artifacts — the Lakehouse, Warehouses etc. Each of these is treated as a single entity in Purview, inventoried automatically after a scan completes. Sub-item level metadata — and this is the exciting part — now extends into the Lakehouse itself. Purview can now scan tables (Delta format) and files within a Lakehouse, surfacing column-level detail, data types, and structural information directly in the Unified Catalog. For a data steward or data consumer, this is the difference between knowing "a Lakehouse called Sales Gold exists" and knowing "that Lakehouse contains a Delta table called fact orders with 14 columns including order date (date) and revenue (decimal)." That distinction matters enormously for data discoverability, data contracts, and onboarding new consumers onto your data products. Setting It Up — Simpler Than You Think Connecting Purview to your Fabric tenant in the same Microsoft Entra tenancy is refreshingly straightforward. At a high level, the steps are: Register your Fabric tenant as a data source in the Purview Data Map. Create a security group in Microsoft Entra ID, add your Purview Managed Identity (MSI) or service principal to it, and grant that group read-only Admin API access in the Fabric tenant admin portal. Enable the "Enhance admin APIs responses with detailed metadata" setting in the Fabric Admin portal. This is easy to miss but critical — without it, sub-item scanning won't function correctly. Configure and schedule your scan, scoping it to all workspaces or a targeted subset. Support for Managed Identity authentication is now available, which simplifies credential management for teams already invested in Azure's identity infrastructure. One practical note: if you are running multiple Fabric or Power BI scans simultaneously, you may encounter rate limiting. The recommended approach is to stagger scans across different time windows rather than running them in parallel. What You Can Do With It Once scanned, the metadata surfaces in Purview's Unified Catalog, where your teams can browse by source type, workspace, or Fabric experience, and search for specific assets by name, description, or other attributes. This makes it genuinely easy for data consumers to find and evaluate data before requesting access! From a governance standpoint, this unlocks several capabilities that matter to modern data teams: Data discoverability — analysts and data scientists can find Lakehouse tables in the catalog without relying on tribal knowledge or chasing down the engineer who built the pipeline six months ago. Are you ready to setup Microsoft Fabric scan in Microsoft Purview? Head over to the Microsoft Purview Portal and select Data Map. Learn more in the Register Microsoft Fabric in Microsoft Purview documentation.Microsoft Purview enables developers with strong data security across AI apps and agents
Today, developers are at the center of a new wave of innovation—building AI applications and agents that are deeply connected to enterprise data. But with this opportunity comes a new and complex set of security challenges. AI systems operate across cloud platforms, third-party services, and even local and on-premises development environments, interacting dynamically with sensitive data such as customer records, financial information, and intellectual property. Traditional security approaches weren’t designed for this level of scale, autonomy, or fluid data movement—leaving developers to navigate fragmented tools, unclear policies, and the risk of unintentionally exposing sensitive information. At the same time, expectations are rising. Organizations need to ensure that AI applications and agents are compliant, auditable, and secure by default on an enterprise-level—not retrofitted after deployment. But for developers, adding security often means additional complexity, custom integrations, and slower time to market. This tension between speed and control has become one of the biggest barriers to moving AI from experimentation into production. Microsoft Purview is designed to help with this challenge by embedding data security and compliance controls across the development cycle. Purview provides a consistent way to govern how data is accessed, used, and shared—without requiring developers to become security experts. The result is a simpler path to building AI systems that are secure, compliant, and enterprise-ready by design. Extending data security and compliance to local agents and claws Local and endpoint agents, built in platforms such as GitHub Copilot CLI and OpenClaw, introduce a new class of data security challenges as they operate outside traditional control planes and directly on user machines. Unlike cloud systems, these agents can access local files, credentials, terminals, and enterprise apps simultaneously—often moving data across tools and environments. This expands data risks, from sensitive data being unintentionally stored, copied, or shared, to API keys and tokens being exposed, and autonomous workflows triggering data movement without explicit user intent. At the same time, many existing security controls were designed for browser or cloud-based activity, leaving a growing blind spot at the endpoint where agents are increasingly running. The result is a widening gap between how developers build agents to operate locally in the users machines, and how organizations can detect, govern, and protect the data those agents interact with. Microsoft Security and Windows are integrating management and security capabilities directly into the local agents’ development workflow, enabling security as an architectural guarantee rather than an implementation choice. At Build, we are thrilled to be extending Purview visibility and protection capabilities to local agents developed on GitHub Copilot CLI, Claude Code, OpenAI Codex, and OpenClaw - in Public Preview. Unlike traditional cloud applications, these agents operate closer to the data and often create new risks for data exposure. Purview addresses this challenge across all types of agent interactions with a clear, simplified set of scenarios: ▪ Observability: Visibility on Purview Data Security Posture Management (DSPM) across agent inventory, as well as into how local agents interact with sensitive data—across prompts, responses, and actions. ▪ Runtime data protection: Purview Data Loss Prevention (DLP) controls enforced directly into the agent execution flow, inspecting prompts and tool calls in real time to prevent sensitive data exfiltration. ▪ Agentic risk detection: Risky or anomalous agent behaviors detected through Insider Risk Management (IRM) signals, helping teams detect unsafe interactions early. ▪ Audit: Comprehensive, end-to-end logging of all local agent interactions—capturing prompts, responses, data access, and actions for data context. For example, a developer is using a local coding agent to generate code and accidentally includes sensitive credentials in a prompt. AI observability in DSPM surfaces the interaction and shows what data the agent accessed. DLP detects the sensitive data in real time and blocks it from being sent or processed (or sensitive files from being accessed and exfiltrated). At the same time, agentic risk detection flags the session as high risk based on the behavior pattern. All of this activity is captured in audit logs, enabling the security team to investigate and take action quickly. Developers and security teams gain visibility into agent activity and data interactions, while policies prevent sensitive data leakage. This ensures consistent security outcomes across both cloud and endpoint environments, without disrupting developer workflows. Strengthening visibility and controls for Foundry agents Foundry gives developers a central place to build and manage AI agents, but it also creates a need for data security context directly in that workflow—especially as prompts, model interactions, and downstream actions increasingly involve sensitive enterprise data. At Build, we are excited to announce the expansion of the Foundry integration with Purview. This includes Purview DLP runtime controls for prompt processing in Foundry, in Public Preview. As agents and applications built on Foundry increasingly interact with sensitive data, Purview ensures those interactions are governed by trusted controls, identifying Sensitive Information Types (SITs) in real time to detect and protect confidential data embedded in prompts. For example, if a user includes customer PII or financial data in a prompt, Purview can automatically identify the sensitive content and block that prompt from being processed by the model. This ensures that all Foundry apps and agents, regardless of how they’re built or deployed, inherit consistent data protection – allowing organizations to reduce risk of inadvertent data exposure, centralize compliance enforcement across AI workloads, and confidently scale AI adoption knowing sensitive data is protected by design. We’re also building up on the Purview coverage for Foundry shared at the last Microsoft Ignite by announcing Purview insights embedded directly into the Foundry Control Plane, in General Availability, bringing rich data security context to the plane where developers already work. Purview surfaces crucial signals—such as SITs detected in the agentic interactions, % of agentic interactions involving sensitive data, and spread of high-risk users — so Foundry admins can know how AI apps and agents are built in their environment. This shift enables developers to make faster, better decisions in the moment, reducing rework and closing security gaps early on. For customers, the value is clear: stronger security by design and at enterprise scale, accelerated development cycles, and reduced risk of data leaks or compliance issues—without slowing down innovation. Innovating for developers everywhere, at the pace of AI growth Microsoft is also expanding Purview’s reach across the broader developer ecosystem. New integrations help organizations apply consistent oversight to AI tools and platforms developers already use, without adding separate compliance workflows. GitHub Copilot is a critical productivity layer for developers, accelerating how code is written and shipped—making it equally important that developer interactions with GitHub Copilot are governed and secured with the same rigor as enterprise data. Microsoft Purview now extends data governance and compliance capabilities to GitHub Copilot interactions, in Public Preview, enabling GitHub Enterprise customers with Entra SSO to stream audit logs directly into Purview. This brings centralized visibility for AI activity, allowing security and compliance teams to analyze GitHub Copilot agent session activity alongside other AI workloads. With this native integration into GitHub workflows, Purview audits Copilot activity across repositories, pull requests, and developer sessions—ensuring AI-generated code aligns with enterprise data policies, compliance requirements, and secure development standards. By integrating Purview into existing workflows, organizations can govern GitHub AI usage without building parallel pipelines—reducing complexity while ensuring consistent compliance coverage across their entire data estate. Today’s AI agents aren’t built in just one ecosystem—they span custom apps, third-party platforms, and open-source frameworks. Without consistent controls, this creates blind spots where sensitive data can be exposed outside enterprise guardrails. That’s why extending Purview protection beyond Microsoft environments is critical: it ensures developers can apply the same data security, DLP policies, and compliance controls to any agent, anywhere—so innovation can scale without increasing risk. Developers already use Microsoft Purview APIs to embed data protection into enterprise workflows. Today, we’re introducing the Microsoft Purview SDK for .NET — a simple, drop-in toolkit that brings Purview capabilities directly into any application, in Public Preview. Instead of weeks spent wiring APIs, authentication, and error handling, developers can add content scanning, DLP checks, and sensitivity labeling in just a few lines of code. The SDK handles the heavy lifting — including auth, retries, caching, and telemetry — so teams can focus on building experiences. For AI apps and agents built outside of the Microsoft AI platforms, SDK adds built-in support and can evaluate prompts and responses in real time against DLP and content policies — helping prevent data exposure at runtime without custom logic. Designed for both real-time and asynchronous patterns, and for authenticated or anonymous flows, the SDK also feeds activity back into Purview to give security teams centralized visibility and control. The bottom line is- the Microsoft Purview SDK enables developers to build AI apps and agents that are secure and compliant by default — cutting integration time from weeks to days while ensuring data protection scales with AI. The SDK will be available in public preview within the next month. Together, these announcements represent a significant step forward in how developers build secure AI systems. Microsoft Purview is no longer just a data security and compliance solution—it is a first-class layer of the development process by protecting data across AI applications and agents, and enables a bridge between developers and security teams. As AI becomes more agentic, distributed, and deeply connected to enterprise data, the need for built-in security will only grow. With Purview, developers no longer must choose between speed and security—they can build both into every application from the start Getting connected with Microsoft Purview and learn more Learn more about Microsoft Purview on our website and Microsoft Learn. Explore Agent 365. Try Microsoft Purview data security. Learn more about Microsoft Purview SDK.Safeguarding Sensitive Data in Microsoft 365 Copilot Interactions: DLP for Microsoft 365 Copilot
Microsoft 365 Copilot is redefining how organizations work, bringing the power of generative AI directly into our secure productivity tools. As Copilot adoption accelerates, we’ve heard that you want more control over how your sensitive data can be used in interactions with Copilot. At Ignite 2025, Microsoft announced a major enhancement: Microsoft Purview Data Loss Prevention for Microsoft 365 Copilot to safeguard Microsoft 365 Copilot and Copilot Chat prompts, now entering General Availability. Even better, this capability is included for all users of Microsoft 365 Copilot and Copilot Chat. Why DLP for Copilot Prompts Is a Game-Changer As organizations adopt Copilot, their ways of sharing, creating, and interacting with data expand. With just a prompt, users can have Copilot summarize documents, analyze spreadsheets, or help brainstorm presentations. However, it raises an important question: what if the prompt includes sensitive information, like project code names, financial account numbers, health records, or other sensitive data? Over the last 2 years, Microsoft has been building a set of Data Loss Prevention (DLP) controls specifically designed for Copilot. Below is a quick overview of these related capabilities — ranging from already available to newly in preview — before we dive deep into today's GA announcement: Prevent Copilot processing of files & emails based on sensitivity labels In November 2024, Microsoft introduced the ability to create a DLP policy to restrict Microsoft 365 Copilot and Copilot Chat from processing sensitive files and emails using Sensitivity Labels for grounding data. This capability gives you control over whether content with the sensitivity labels you specify is restricted from being used in Microsoft 365 Copilot and Copilot Chat to generate summaries and responses. Prevent web searches for prompts containing Sensitive Information Types (SITs) The latest feature entering Public Preview is DLP for Microsoft 365 Copilot and Copilot Chat to prevent web searches for prompts containing sensitive data. This real-time control helps organizations mitigate data leakage and oversharing risks by preventing Microsoft 365 Copilot and agents from using sensitive data for external web searches. If a sensitive information type (SIT) is detected in a user prompt, Copilot can still leverage your enterprise data to form a response without sending the sensitive data to external search engines for web grounding. This capability extends to Microsoft 365 Copilot and agents built in Copilot Studio that are published to Microsoft 365 Copilot. DLP to Safeguard Copilot Prompts with Sensitive Information Types (SITs) The rest of this blog focuses on a key addition to this capability set: DLP for Microsoft 365 Copilot + Copilot Chat prompts to prevent processing of prompts containing sensitive information, now entering General Availability. Unlike the web search capability above, which prevents sensitive data from being sent externally during a web query, this capability evaluates the user’s text input directly, before processing occurs, to determine whether both enterprise data and web grounding can proceed. This feature uses Sensitive Information Types (SITs) as a condition within a Purview DLP policy to assess whether a user prompt sent to Copilot contains sensitive data, even if the data is unlabeled. With DLP for Copilot prompts, a user’s text input is scanned in real time for SITs, whether built-in (like Social Security Numbers, credit card numbers, etc.) or custom-defined by your organization (such as confidential terms or project names). If a text prompt contains one of the SITs you specify, Copilot restricts processing, halts any Graph or web grounding, and displays a clear message to the end user that the request cannot be completed. A user enters a prompt in Microsoft 365 Copilot Chat containing sensitive information. How DLP for Copilot Protects Prompts: Real-Time, Intelligent Protection The new DLP capability integrates seamlessly with Microsoft Purview, leveraging its powerful data classification & detection engine for sensitive information types. Here’s how it works: Input: When a user submits a prompt, Copilot checks the prompt for sensitive information using built-in or organization-defined sensitive information types (SITs). Immediate Action: If a SIT is detected, Copilot restricts the prompt from being processed. No AI response is generated, and no data is sent for Graph or web grounding. Output: Users receive a clear notification that their request cannot be completed due to company policies. This real-time protection ensures that sensitive data is not leaked or overshared, even as users explore new ways to work with AI. Setting Up DLP for Copilot Prompts: Data Security Admin Experience The easiest way to get started is through the new Microsoft Purview Data Security Posture Management (DSPM) portal, which provides a guided, one-click setup experience: 1. In Purview, go to Solutions > DSPM (preview) 2. Select the "Prevent data exposure in Microsoft 365 Copilot and Microsoft Copilot interactions" objective. 3. Follow the guided workflow and apply the recommended one-click DLP policy. The policy starts in simulation mode so you can review activity before enforcing it. Alternatively, you can configure and customize this policy directly from the Purview DLP portal Policies page or enable it from the Microsoft 365 Admin Center. view the remediation plan. view policy details and review. Then click the button, create a custom policy in DLP simulation mode to protect sensitive data referenced in Microsoft 365 Copilot and Microsoft Copilot. the confidence level and instance count. Practical Scenarios: Protecting What Matters Most Protect PII, financial data, and intellectual property: Financial institutions can block prompts containing deal terms, account numbers, or other sensitive data, preventing leaks through AI interactions. Similarly, healthcare organizations can safeguard patient information, and manufacturers can secure intellectual property and trade secrets from exposure, along with many other practical use cases. Once the prompt is detected and blocked, Microsoft Graph grounding and Bing web grounding is restricted. Safeguard sensitive non-public information: Imagine an organization involved in a confidential merger. By using DLP for Copilot prompts, administrators can set up a custom SIT that includes the project’s code name. If a user asks Copilot about the merger using the project’s code name, their request will be blocked, keeping sensitive information secure and protected. Visibility into DLP for M365 Copilot Prompts When a user’s prompt triggers a DLP policy, notifications and alerts are surfaced directly in the Microsoft Purview and Defender portals for security administrators. These alerts provide detailed information about which policy was activated, the type of sensitive information detected, and the context of the attempted Copilot interaction. Using these alert queues in Purview and Defender XDR, administrators can efficiently track policy activity, investigate potential incidents, and refine DLP rules to better align with organizational needs. The ability to review historical alerts and track ongoing enforcement empowers admins to maintain strong data security and proactively safeguard sensitive information. Defender XDR portal investigation of prompt DLP based incident. Takeaways The introduction of this latest enhancement to DLP for Copilot represents a key advancement in secure Copilot deployment and adoption. By empowering organizations to block sensitive data at the prompt level, Microsoft is helping customers unlock the full potential of Copilot, without compromising security or compliance. This innovation reflects Microsoft’s commitment to responsible AI, continuous improvement, and customer-driven development. As Copilot evolves, so will the tools to protect your data, ensuring that productivity and security go hand in hand. For more details, stay tuned for updates to the Product Roadmap and Learn documentation. Learn about using DLP to protect interactions with Microsoft 365 Copilot and Copilot Chat Learn about the default DLP policy for Microsoft 365 Copilot location | Microsoft Learn Permissions to create or edit a DLP policy to safeguard Microsoft 365 Copilot and Copilot Chat Learn about the new Microsoft Purview Data Security Posture Management (DSPM) | Microsoft Learn Roadmap Item: DLP for Microsoft 365 Copilot to safeguard prompts Roadmap Item: DLP to safeguard web search in Microsoft 365 CopilotSecuring AI Agents End‑to‑End: Connecting Purview DSPM, Agent 365, and the AI Security Dashboard
The Challenge: Organizations deploying Microsoft Copilot and custom AI agents face a critical gap: security visibility is fragmented across data protection, identity governance, and threat detection tools. While Microsoft provides powerful capabilities through Purview Data Security Posture Management (DSPM), Agent 365, and the AI Security Dashboard, practitioners often struggle to understand how these components work together to deliver unified AI security posture management. This blog provides an architectural and operational blueprint for connecting these three pillars into a cohesive security framework that security architects can implement today. The Three Pillars: Capabilities Overview Microsoft Purview DSPM for AI Purview DSPM extends data‑centric security controls to AI interactions. Its key capabilities include: Sensitivity labels with EXTRACT usage rights that govern whether AI agents can read and process sensitive content Data Loss Prevention (DLP) policies that block or audit AI interactions involving confidential data across Copilot, SharePoint, OneDrive, and Teams Comprehensive audit logging that captures AI‑to‑data interactions, including user identity, agent identity, data classification, and the action taken Insider Risk Management integration that detects anomalous agent behavior patterns, such as bulk or unusual data access DSPM operates at the data layer, answering a foundational question: What sensitive information can this agent access, and what is it doing with that data? Microsoft Agent 365 Agent 365 provides a unified control plane for governing AI agent identity, access, and lifecycle across the Microsoft 365 ecosystem. Core components include: Agent Registry, backed by Entra Agent IDs, providing a unique identity for every Copilot Studio agent, custom agent, and supported third‑party AI integration Conditional Access policies that enforce real‑time access controls based on agent identity, user context, device compliance, and risk signals Centralized observability, with dashboards showing agent‑to‑agent interactions, agent‑to‑human conversations, and near real‑time telemetry Governance workflows that support agent approval, lifecycle management, suspension, and decommissioning Agent 365 operates at the identity and control layer, answering: Which agents exist, who authorized them, and what access boundaries are enforced? AI Security Dashboard The AI Security Dashboard aggregates security signals from Entra, Purview, and Defender to provide a unified risk view across all AI assets. It delivers: AI asset inventory, cataloging Copilot instances, custom agents, and third‑party models with associated risk context Misconfiguration detection, identifying agents with excessive permissions, missing conditional access policies, or DLP coverage gaps Attack path visualization, showing how compromised agents could pivot to sensitive data or escalate privileges Integration with Microsoft Security Copilot, enabling natural‑language investigation of AI security risks and incidents The Dashboard operates at the aggregation and recommendation layer, answering: What is my overall AI security posture, and where should remediation be prioritized? The Unified Architecture: How Signals Flow End-to-End Understanding the technical integration requires mapping how identity, data, and security signals flow across these three systems. Identity Foundation (Microsoft Entra): Every AI agent is assigned a unique Entra Agent ID at creation. This identity becomes the anchor for all security controls—conditional access policies in Agent 365, audit attribution in Purview, and risk correlation in the AI Security Dashboard. When a Copilot Studio agent is deployed, Entra automatically registers it with Agent 365 and propagates identity metadata to connected security services. Data Interaction Telemetry (Microsoft Purview): When an agent accesses SharePoint files, reads emails, or queries structured data, Purview captures detailed audit events that include agent identity, user context, data classification labels, and enforcement outcomes. These events flow into Purview’s unified audit log and are accessible through the Compliance portal, Microsoft Graph, and SIEM integrations. Crucially, Purview enforces sensitivity labels with EXTRACT usage rights—if a document is labeled Confidential without EXTRACT permission, the agent’s request is blocked before content reaches the AI model. Control Plane Enforcement (Agent 365): Agent 365 applies identity‑based governance by evaluating Entra signals and surfaced risk indicators. During policy evaluation, the control plane verifies whether the agent is registered, whether the invoking user satisfies authentication requirements, and whether recent signals (such as DLP violations) warrant blocking execution. Agent 365 also provides observability views that correlate agent activity with security events, helping administrators identify unmanaged or unauthorized (“shadow”) agents. Aggregated Risk View (AI Security Dashboard): The AI Security Dashboard correlates telemetry from: Entra — conditional access decisions, authentication anomalies, and privileged identity usage Purview — DLP violations, sensitivity label mismatches, and Insider Risk Management signals Defender — threat detections, application posture assessments, and suspicious activity indicators These signals are correlated by agent identity and time, then surfaced as risk cards with contextual severity and recommended remediation actions. The Dashboard does not replace the underlying tools; instead, it provides a consolidated view that helps teams focus on the most impactful risks. The diagram below illustrates how identity, data, and threat signals flow across the three AI security pillars. Figure 1: End‑to‑end AI security architecture. Enforcement happens at the data layer (Purview) and identity layer (Agent 365 via Entra). The AI Security Dashboard aggregates—rather than replaces—underlying security controls. From Architecture to Action: Telemetry & Enforcement Flow Understanding architecture is essential—but practitioners need to know when and where enforcement occurs during a real agent invocation. The sequence below illustrates runtime interaction between a user, an AI agent, and the three security pillars. The Critical Distinction: Two Enforcement Layers Enforcement occurs at two distinct points in the request lifecycle. First, Microsoft Entra validates agent identity and evaluates conditional access policies before execution begins. If the agent is not registered, if the user fails authentication requirements, or if policy conditions require blocking, execution is denied immediately. Second, when execution is permitted, Purview DSPM enforces data access controls inline. Every attempt to access documents, emails, or structured data is evaluated in real time. If a document is labeled Confidential without EXTRACT rights, Purview blocks the request and returns no sensitive content to the agent. Telemetry Generation Across the Stack Each step produces structured telemetry. Entra logs authentication attempts and policy decisions. Purview records AI interaction audit events, including enforcement outcomes. Agent 365 correlates identity and behavior signals to maintain agent posture and observability. These combined signals are surfaced in the AI Security Dashboard, which correlates activity across time and identity to present prioritized risk insights. Make the “where enforcement happens” distinction explicit (data vs. identity). Figure 2: Purview enforces data controls inline, Agent 365 enforces identity and execution controls, and the AI Security Dashboard correlates signals for prioritization. Practitioner Scenario: Detecting and Blocking Agent Data Exposure Context: Your organization deploys a custom Copilot Studio agent to summarize sales proposals stored in SharePoint. Several documents contain customer PII labeled "Highly Confidential" with no EXTRACT usage rights granted. Incident Timeline: Agent Data Exposure Detection → Remediation Detection The agent attempts to access SharePoint files through Microsoft Graph. Purview DSPM evaluates sensitivity labels and identifies restricted documents. A DLP policy blocks access and logs a violation with full context. The audit event appears in the Purview unified audit log within minutes. Visibility Agent 365 flags the blocked interaction in its observability dashboard. The AI Security Dashboard surfaces a High‑severity risk card titled “Agent accessing restricted data.” Security teams investigate the agent using Security Copilot to determine scope and recurrence. Remediation An administrator applies an Entra conditional access policy to suspend the agent. Data permissions are adjusted to restrict access or explicitly grant EXTRACT rights where justified. The AI Security Dashboard reflects a reduced risk score once controls are validated. Outcome: The incident is contained quickly, audit evidence is preserved, and the agent is restored with least‑privilege access—without disrupting legitimate business workflows. Figure 3: A single DLP violation triggers coordinated detection, investigation, and remediation across Purview, Agent 365, and the AI Security Dashboard within 30 minutes. Division of Responsibility: What Each Tool Does Tool Primary Function Key Signals Enforcement Capability Purview DSPM Data-layer protection and audit Sensitivity labels, DLP violations, data access patterns Blocks API calls violating DLP or label policies Agent 365 Identity and lifecycle governance Agent registry, conditional access hits, observability telemetry Denies agent invocation based on Entra policies AI Security Dashboard Unified risk aggregation Cross-product signals from Entra, Purview, Defender No direct enforcement—provides recommendations and prioritization Critical Distinction: Enforcement happens at two layers—Purview blocks data access violations, while Agent 365 (via Entra) blocks agent invocation. The Dashboard does not enforce policies but accelerates investigation and remediation by correlating signals that would otherwise require manual analysis across three separate consoles. Key Takeaways for Practitioners Agent identity is the integration anchor. Every security control—DLP policies, conditional access, audit logs, risk scoring—relies on Entra Agent IDs. Ensure all agents are properly registered in Agent 365 before production deployment. Purview enforces at the data layer, Agent 365 at the identity layer. Use both—Purview prevents unauthorized data exfiltration, while Agent 365 prevents unauthorized agent execution. Neither is redundant. The AI Security Dashboard is for prioritization, not replacement. Continue using Purview Compliance Portal for detailed DLP investigations and Agent 365 registry for operational monitoring. Use the Dashboard to identify which risks warrant immediate attention. Audit logs are your ground truth. All three tools consume Purview audit events. Integrate these logs with Microsoft Sentinel or your SIEM for long-term retention and advanced threat hunting. Shadow agents are your blind spot. Regularly audit the Agent 365 registry against actual AI deployments (Copilot Studio, Azure OpenAI, third-party integrations) to identify unregistered instances. As AI agents become embedded in everyday work, security teams must move beyond feature‑level understanding and adopt an end‑to‑end enforcement mindset. The combination of Purview DSPM, Agent 365, and the AI Security Dashboard provides the building blocks—but value is realized only when they are implemented as a unified model. How are you governing AI agents in your environment today? Share your experiences and patterns in the comments—especially where identity, data, and security signals intersect.Security Dashboard for AI: 3 Ways CISOs Drive Impact Today
AI is reshaping the enterprise and, with it, the threat landscape. Today's organizations face new threats with AI agents that modify configurations, execute workflows, and access data without direct human oversight. As a result, the gap between AI adoption and AI governance is widening, and CISOs face growing challenges to maintain visibility, control, and compliance across an increasingly complex ecosystem. As AI becomes embedded across the enterprise, CISOs face four key challenges: Scale without visibility: Over 75% of enterprises surveyed by PWC report they are already adopting AI agents. ¹ At the same time, over 80% of security teams surveyed by Nokod report visibility gaps into the applications and AI agents created within their organization. ² Rapid AI proliferation and evolving regulations make unified visibility across AI platforms, apps, and agents critical for CISOs. Fragmentation: Organizations rely on multiple siloed tools for AI asset visibility, making oversight fragmented and inefficient. According to Gartner’s 2024 survey of 162 enterprises, organizations use 45 cybersecurity tools on average. Expanding AI risk: AI proliferation is rapidly increasing the attack and risk surface, with the surge of AI-generated identities. By 2027, 4 out of 5 organizations will face phishing attacks powered by AI-generated synthetic identities, according to IDC. ³ This makes it harder for CISOs to track emerging threats, unmanaged assets, and shifting risk patterns. Overload: Alert fatigue is now a top challenge, with organizations now receiving an average of 2,992 security alerts daily, yet 63% go unaddressed. ⁴ Increasing AI risk without a way to prioritize what matters most compounds pressure on CISOs. In conversations between Microsoft and CISOs, one common need emerged: a single place to view integrated AI risk across the enterprise. To address these growing challenges, we are excited to provide CISOs with the Security Dashboard for AI, which recently became generally available. This unified dashboard aggregates posture and real-time risk signals from Microsoft Defender, Entra, and Purview into one unified, executive-level view of AI posture, risk, and inventory across agents, apps, and platforms. The Security Dashboard for AI helps CISOs: Gain unified AI risk visibility: Discover AI agents and applications and continuously monitor posture across the environment Prioritize critical risks: Correlate signals across identity, data, and threat protection to surface the most urgent issues Drive risk mitigations: Investigate activity and take action to help reduce exposure across the AI ecosystem The dashboard is capable of aggregating and surfacing AI risks from across Microsoft Defender, Entra, Purview - including Microsoft 365 Copilot, Microsoft Copilot Studio agents, and Microsoft Foundry applications and agents as well as cross-platform AI risks with Microsoft network-based or SDK-enabled integrations, and MCP servers. This supports comprehensive visibility and control, regardless of where applications and agents are built. As you activate Microsoft Security for AI capabilities, you can gain richer visibility into different aspects of your AI risk posture. Figure 1: Security Dashboard for AI in browser Getting Started with the Security Dashboard for AI The Security Dashboard for AI is provided at no additional cost to customers already using Defender, Entra, and/or Purview to protect their AI innovation. Based on how early adopter CISOs are using the dashboard, here are three ways you can start leveraging the dashboard today. 1. Manage Daily AI Risk Beyond reporting, you must stay hands-on with AI risks, scanning for emerging issues, verifying asset governance, and delegating remediations. The Security Dashboard for AI consolidates daily operations into a single pane of glass, surfacing critical alerts, unmanaged assets, and emerging risks. Use the dashboard as a daily AI risk radar, enabling rapid triage and ensuring you focus on the most urgent threats. Scan and triage daily AI risk: Start each day by identifying and prioritizing the highest-risk AI exposures. Risks are prioritized on severity reported by underlying security tools, helping you focus on the most critical exposures. Track AI asset inventory and monitor agent sprawl: Use the Inventory page to gain comprehensive visibility into all AI assets. Identify newly registered assets to mitigate the risk of shadow or unmanaged IT and surface inactive agents to proactively monitor and control agent sprawl. Delegate tasks for remediation: Move from insight to action by delegating tasks to your security team with easy click delegation. Delegation routes ownership via email or Microsoft Teams with notifications, due date, and ownership tracking. Delegate actions to specific roles such as global admin and AI administrator, without granting full access to underlying tools. Figure 2: Security Dashboard for AI risk page 2. Guide Briefings with Security Teams You require up-to-date intelligence to guide conversations with Security Teams about what is happening across the AI estate. The Security Dashboard for AI helps you anchor discussions in specific risks, trends, and ownership gaps surfaced in the data. The dashboard becomes a conversation driver, helping you ask the right questions about risk and security posture, to help ensure you and your team are triaging the right priorities. Because the dashboard consolidates signals from Defender, Entra, and Purview, both CISO and security teams operate from the same facts, enabling more outcome-driven discussions and faster prioritization, so you can shift the conversations from status updates to targeted action planning. Prioritize top AI Risk: Use the dashboard to help you prioritize the AI risk that matters the most. In preparation for team meetings, use Microsoft Security Copilot to explore AI risks, agent activity, and security recommendations via prompts to strengthen your AI security posture. With your team, take a closer look at risk vectors like data leakage, oversharing and unethical behavior, and discuss what actions need to be taken. Review Security Recommendations: Create a routine with your security team to review the recommended Microsoft security actions and track your progress over time. Across regular team check‑ins, review what has been addressed, what remains open, and which actions require follow‑up so you are prepared to respond to regulatory, audit, or executive questions with up‑to‑date metrics. Figure 3: Security Dashboard for AI inventory page Figure 4: Security Dashboard for AI delegation 3. Executive Reporting Reporting to the board on AI security posture has historically meant weeks of manual data gathering across multiple tools. The Security Dashboard for AI streamlines the data collection process with a single source of truth for AI risk, enabling confident, data-backed insights for your board presentations and conversations. Early adopters confirm the value and are using it for quarterly executive briefings. Prepare for Board Discussions: Use the dashboard to help get the right insights at the right altitude to help you prepare for discussions with your board. The Overview page aggregates identity, data security, and threat protection signals from Defender, Entra, and Purview into an AI risk scorecard with risk factors. The embedded Security Copilot AI-powered insights provide suggested prompts with risk assessments, summaries, and recommendations to help you prioritize what matters most. Extend Observability to Executive Stakeholders: Authorize AI risk follow‑ups to the appropriate security, identity, or governance owners using Microsoft Teams or email. Distribute visibility across GRC lead, AI governance, and IT leaders, while maintaining executive‑level oversight. Figure 5: Security Dashboard for AI Copilot prompt gallery Next Steps The Security Dashboard for AI helps CISOs manage AI risk faster, more confidently and more collaboratively with their team. Defender, Entra, and Purview signals are surfaced in a single pane of glass, providing observability across your AI estate. Drive faster triage, use data to support board-level discussions about AI risk, and enable coordinated action with integrated insights, recommendations, and delegation to help accelerate remediation across existing security workflows. The Security Dashboard for AI is generally available now. If your organization uses Microsoft Defender, Entra, and/or Purview, you already have access, no additional licensing is required. Visit ai.security.microsoft.com to access the dashboard directly, or navigate to it from the Defender, Entra, or Purview portals. Learn more about the Security Dashboard for AI on the MS Learn page and the Security Dashboard for AI Security Blog. Discover new features in the Security Dashboard for AI such as the Security Reader role, new delegation flow, and new identity risk section here. ¹AI agent survey. PwC, May 2025 ²Security Teams Taking on Expanded AI Data Responsibilities. Bedrock Data, March 2025 ³IDC FutureScape: Worldwide Security and Trust 2026 Predictions, November 2025 ⁴2026 State of Threat Detection and Response Report. Vectra AI, February 2026Security Dashboard for AI - Now Generally Available
AI proliferation in the enterprise, combined with the emergence of AI governance committees and evolving AI regulations, leaves CISOs and AI risk leaders needing a clear view of their AI risks, such as data leaks, model vulnerabilities, misconfigurations, and unethical agent actions across their entire AI estate, spanning AI platforms, apps, and agents. 53% of security professionals say their current AI risk management needs improvement, presenting an opportunity to better identify, assess and manage risk effectively. 1 At the same time, 86% of leaders prefer integrated platforms over fragmented tools, citing better visibility, fewer alerts and improved efficiency. 2 To address these needs, we are excited to announce the Security Dashboard for AI, previously announced at Microsoft Ignite, is now generally available. This unified dashboard aggregates posture and real-time risk signals from Microsoft Defender, Microsoft Entra, and Microsoft Purview - enabling users to see left-to-right across purpose-built security tools from within a single pane of glass. The dashboard equips CISOs and AI risk leaders with a governance tool to discover agents and AI apps, track AI posture and drift, and correlate risk signals to investigate and act across their entire AI ecosystem. Security teams can continue using the tools they trust while empowering security leaders to govern and collaborate effectively. Gain Unified AI Risk Visibility Consolidating risk signals from across purpose-built tools can simplify AI asset visibility and oversight, increase security teams’ efficiency, and reduce the opportunity for human error. The Security Dashboard for AI provides leaders with unified AI risk visibility by aggregating security, identity, and data risk across Defender, Entra, Purview into a single interactive dashboard experience. The Overview tab of the dashboard provides users with an AI risk scorecard, providing immediate visibility to where there may be risks for security teams to address. It also assesses an organization's implementation of Microsoft security for AI capabilities and provides recommendations for improving AI security posture. The dashboard also features an AI inventory with comprehensive views to support AI assets discovery, risk assessments, and remediation actions for broad coverage of AI agents, models, MCP servers, and applications. The dashboard provides coverage for all Microsoft AI solutions supported by Entra, Defender and Purview—including Microsoft 365 Copilot, Microsoft Copilot Studio agents, and Microsoft Foundry applications and agents—as well as third-party AI models, applications, and agents, such as Google Gemini, OpenAI ChatGPT, and MCP servers. This supports comprehensive visibility and control, regardless of where applications and agents are built. Prioritize Critical Risk with Security Copilots AI-Powered Insights Risk leaders must do more than just recognize existing risks—they also need to determine which ones pose the greatest threat to their business. The dashboard provides a consolidated view of AI-related security risks and leverages Security Copilot’s AI-powered insights to help find the most critical risks within an environment. For example, Security Copilot natural language interaction improves agent discovery and categorization, helping leaders identify unmanaged and shadow AI agents to enhance security posture. Furthermore, Security Copilot allows leaders to investigate AI risks and agent activities through prompt-based exploration, putting them in the driver’s seat for additional risk investigation. Drive Risk Mitigation By streamlining risk mitigation recommendations and automated task delegation, organizations can significantly improve the efficiency of their AI risk management processes. This approach can reduce the potential hidden AI risk and accelerate compliance efforts, helping to ensure that risk mitigation is timely and accurate. To address this, the Security Dashboard for AI evaluates how organizations put Microsoft’s AI security features into practice and offers tailored suggestions to strengthen AI security posture. It leverages Microsoft’s productivity tools for immediate action within the practitioner portal, making it easy for administrators to delegate recommendation tasks to designated users. With the Security Dashboard for AI, CISOs and risk leaders gain a clear, consolidated view of AI risks across agents, apps, and platforms—eliminating fragmented visibility, disconnected posture insights, and governance gaps as AI adoption scales. Best of all, the Security Dashboard for AI is included with eligible Microsoft security products customers already use. If an organization is already using Microsoft security products to secure AI, they are already a Security Dashboard for AI customer. Getting Started Existing Microsoft Security customers can start using Security Dashboard for AI today. It is included when a customer has the Microsoft Security products—Defender, Entra and Purview—with no additional licensing required. To begin using the Security Dashboard for AI, visit http://ai.security.microsoft.com or access the dashboard from the Defender, Entra or Purview portals. Learn more about the Security Dashboard for AI at Microsoft Security MS Learn. 1AuditBoard & Ascend2 Research. The Connected Risk Report: Uniting Teams and Insights to Drive Organizational Resilience. AuditBoard, October 2024. 2Microsoft. 2026 Data Security Index: Unifying Data Protection and AI Innovation. Microsoft Security, 2026
