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AI Core X brings AI inventory, risk, access and governance information into one central workspace.
The platform is being designed to help security, risk and IT teams understand where AI is operating, what it can access and where additional governance or security controls may be required.
Discover and maintain a central view of AI agents, models and connected AI systems operating across the organisation.
AI Visibility
Evaluate AI agents against security, data, access and governance factors to identify areas requiring attention.
Risk Intelligence
Understand the identities, permissions and enterprise resources associated with individual AI agents.
Access Governance
Maintain visibility into important AI activity, permission changes and interactions across connected environments.
Continuous Monitoring
Organise assessments, ownership records, controls and supporting evidence for internal governance and review.
Evidence & Auditability
Connect AI governance with existing identity, security, cloud and collaboration technologies across the organisation.
Connected Ecosystem
Product Preview
Explore how AI Core X is being designed to bring AI inventory, risk, access, activity and governance information together in one central platform.
The interface shown represents planned and emerging platform capabilities. Feature availability varies across pilot, development and roadmap stages.
AI Core X is being designed to create a structured inventory of AI agents and connected systems across enterprise environments.
Each AI asset can bring together ownership, environment, technology, access, risk and governance information, helping teams understand what is operating and who is responsible for it.
Rather than relying on disconnected spreadsheets and manual records, organisations can build a clearer and more consistent view of enterprise AI adoption.
AI Core X is designed to help organisations assess AI agents against relevant security, data, identity and governance considerations.
Risk information can be organised around individual agents, helping teams identify issues such as sensitive data access, excessive permissions, missing ownership or incomplete governance controls.
Bring relevant risk factors together in one place so security and governance teams can understand why an AI agent may require additional review.
Highlight practical governance and security actions that can help teams address identified risks and improve control over AI systems.
AI Core X is being developed to work alongside the Microsoft technologies organisations already use for identity, security, cloud and productivity.
The platform is intended to bring relevant context from existing enterprise systems into AI security and governance workflows.
Connect cloud and AI workload context with platform inventory, ownership, risk and governance information.
Bring identity, authentication and access information into AI agent governance and permission reviews.
Understand how AI agents interact with enterprise productivity, collaboration and organisational information.
Support integration with established Microsoft security and governance controls rather than creating unnecessary parallel systems.
AI Core X is being developed through staged releases. Product previews may include capabilities that are in pilot, actively under development or planned for future releases.
Capabilities currently being evaluated with selected environments and early platform use cases.
Capabilities actively being designed and implemented as part of the evolving AI Core X platform.
Planned capabilities intended to extend platform coverage, integrations and governance workflows over time.
Organisations should be able to clearly understand what AI systems operate across their environment.
AI agents should have defined business and technical accountability throughout their lifecycle.
AI identities and permissions should be limited to the access required for their intended function.
Security and governance attention should be focused where AI activity creates the greatest organisational risk.
AI governance should evolve as technologies, permissions, usage patterns and organisational requirements change.
AI governance should work with existing security and technology environments rather than creating isolated processes.
