According to Deloitte’s 2026 State of AI in the Enterprise research, 74% of respondents expect their companies to be using AI agents at least moderately by 2027, while only 21% report having a mature governance model for agentic AI.
The opportunity presented by generative AI is significant, but so are the governance challenges. Sensitive information may become easier to find when Microsoft Copilot works within a user’s existing permissions. Unmanaged AI tools can also create shadow AI risks if employees use services that have not been assessed or approved by the organisation.
For UK leaders, the objective is to support innovation without weakening control over the organisation’s data, identities and technology estate. This requires more than enabling a product setting. It requires a coordinated approach to data governance, identity protection, monitoring and incident response.
This guide sets out a practical framework for securing Microsoft Copilot through Microsoft Purview, Microsoft Entra, Microsoft Sentinel and managed extended detection and response services.
Securing Microsoft Copilot starts with a clear understanding of responsibility. Microsoft provides the cloud infrastructure, platform security and service-level controls that support its products. The customer remains responsible for how the service is configured, which users can access it, what information those users can reach and how the organisation manages data and identities. This distinction matters because Microsoft Copilot honours existing Microsoft 365 security and data protection controls.
Copilot only accesses information that the user is authorised to access, so existing oversharing and permission weaknesses can have a greater practical impact. AI can therefore expose existing oversharing and permission weaknesses more quickly than traditional search or manual workflows.
Microsoft documentation should be checked for the specific Copilot product in use. Statements about data processing, model training, retention and Microsoft Graph should not be generalised across Microsoft’s entire Copilot portfolio.
AI-related risk extends beyond traditional malware. Organisations should assess how generative AI may affect data exposure, identity compromise, third-party services and operational decision-making.
Common risk areas include:
Copilot may make poorly governed information easier to locate. This does not necessarily create a new permission, but it can increase the practical impact of permissions that were already too broad. A readiness assessment should therefore examine data access, identity controls, user behaviour and operational monitoring together. CyberOne can support this process through a Cyber Security Gap Analysis and Maturity Assessment. The assessment provides a structured way to understand the current security position, identify material gaps and establish a prioritised path towards greater resilience.
Data governance is a foundation for responsible AI adoption because AI services operate within the security context defined by the organisation. If sensitive data is broadly accessible, the organisation may increase the speed and scale at which that information can be discovered, summarised or used.
Before enabling Copilot at scale, organisations should review the data that users can access and the controls applied to it. Microsoft’s security and governance guidance for Microsoft Copilot specifically recommends using Microsoft Purview and SharePoint governance capabilities to assess oversharing risks. This includes examining SharePoint sites, OneDrive accounts, Teams-connected content, guest access, public links, inactive workspaces and inherited permissions.
The review should answer several practical questions:
The objective is not to make all information inaccessible. It is to ensure that access is deliberate, current and aligned with business need.
Microsoft Purview can support security and compliance controls for Microsoft 365 Copilot, including information protection and data loss prevention capabilities. The exact capabilities available will depend on licensing, workload support and tenant configuration. Organisations should define a classification model that reflects the consequences of disclosure. For example, payroll data, customer records, intellectual property, regulated information and strategic plans may require different controls.
Sensitivity labels can then support access and handling policies where the relevant Microsoft services and configurations support them. They should not be treated as a universal mechanism that automatically prevents AI processing in every scenario.
Microsoft documents specific interactions between Copilot, protected information and Purview controls, including scenarios where usage rights or Data Loss Prevention policies affect Copilot's ability to summarise protected content. The organisation must therefore test how labels, encryption, access rights and Copilot capabilities interact in its specific environment.
A practical governance programme should also include:
Managed data security services can also help organisations maintain classification and protection controls over time. CyberOne provides Data Security as a Service focused on protecting information, enforcing data loss prevention policies and improving Microsoft 365 Copilot readiness.
Identity is a central control point in an AI-enabled environment. A compromised account with broad access may allow an attacker to search, summarise or retrieve sensitive information through connected Microsoft services.
Microsoft Entra can support a Zero Trust approach through multifactor authentication, Conditional Access, privileged identity management, identity risk detection and access reviews. Microsoft Copilot itself is built on Microsoft 365 identity and access controls and aligns with Zero Trust principles including strong identity verification and least-privilege access. These controls should be designed around the organisation’s risk profile rather than applied as isolated technical settings.
Permanent administrative access increases the potential impact of an account compromise. Organisations should review privileged roles, remove unnecessary permissions and use time-limited elevation where appropriate.
Regular access reviews should cover:
Reducing standing access limits the potential impact of compromised identities and makes anomalous activity easier to investigate.
Conditional Access policies can be used as another layer of protection around Copilot experiences. For example, Microsoft specifically recommends layering Conditional Access policies alongside role-based access controls for Microsoft Security Copilot. For Microsoft Copilot, organisations should consider how their existing identity and access policies apply to sensitive users, privileged roles and high-risk access conditions.
Phish-resistant multifactor authentication may be appropriate for privileged accounts and other high-value access paths. However, requiring it for every AI session should be treated as a design decision based on risk, user experience and technical feasibility rather than as a universal requirement.
Access from unmanaged devices may also require additional controls. The appropriate approach should reflect the organisation’s risk profile, Microsoft licensing and the specific Copilot experience being deployed.
Configuration controls provide an important foundation, but they do not remove the need for monitoring. Organisations should establish visibility across identity events, data access, risky sign-ins and relevant Copilot activity.
Microsoft Sentinel can help provide security monitoring across the Microsoft environment. The available Copilot telemetry, connectors and detection capabilities should be confirmed for the specific product, licensing model and tenant configuration.
Monitoring should focus on indicators such as:
The purpose is not to treat every unusual prompt as malicious. Legitimate users may have complex workloads and may ask similar questions repeatedly. Detection should combine identity, data access and behavioural signals so that analysts can distinguish normal activity from credible indicators of compromise.
For organisations that need additional operational capacity,Managed eXtended Detection and Response (MXDR) brings together cross-domain visibility, continuous monitoring, expert investigation and coordinated response. CyberOne’s MXDR approach is designed to help organisations detect and contain threats across endpoints, identities, email, applications, networks and cloud environments.
AI adoption should be included in the organisation’s incident response planning.
Relevant scenarios may include:
Response playbooks should define how the organisation will:
These procedures should be tested before a serious incident occurs. The organisation should also define who has authority to suspend access, disable an integration or restrict a Copilot deployment when necessary.
Securing Microsoft Copilot is an ongoing governance and operational discipline rather than a one-time configuration task.
Organisations need a clear view of the data users can access, the identities that access it and the signals available to detect misuse.
A practical readiness programme should bring together:
Microsoft provides the security and governance capabilities organisations need to build a stronger foundation for Copilot, but outcomes still depend on how those capabilities are configured, governed and operated. Microsoft itself recommends assessing oversharing and applying appropriate data security, AI security, compliance and privacy controls when implementing Copilot and agents. CyberOne helps turn those capabilities into measurable cyber resilience through Microsoft-powered consulting, professional services and managed security.
The next step is to assess your organisation’s current cyber security maturity, including the data, identity and monitoring controls that underpin secure AI adoption. A structured assessment can establish the current position, identify priority gaps and create a practical improvement roadmap.