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.
Key Takeaways
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Treat AI security as a shared responsibility. Microsoft manages the underlying cloud service, while the organisation remains responsible for data governance, configuration, identities and user behaviour.
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Review permissions and classify sensitive information before enabling generative AI capabilities at scale.
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Use Microsoft Entra to apply least privilege, strong authentication and risk-based access controls.
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Monitor relevant identity, data access and Copilot activity signals through Microsoft Sentinel and MXDR, subject to available telemetry and configuration.
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Prepare incident response procedures for compromised accounts, inappropriate data access and suspected prompt injection.
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Measure progress through clear governance, operational controls and evidence of improved cyber maturity.
Understanding The Shared Responsibility Model
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.
Identifying AI Risk Profiles
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:
- Excessive or outdated permissions across SharePoint, OneDrive and other Microsoft 365 services
- Sensitive information stored without appropriate classification or protection
- Compromised accounts used to query or retrieve business information
- Prompt injection or malicious instructions embedded in connected content
- Employees using unapproved AI services to process corporate information
- Limited monitoring of AI-related activity and insufficient response procedures
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.
Establishing Data Governance With Microsoft Purview
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:
- Which users and groups can access sensitive information?
- Are guest accounts and external sharing still required?
- Are public or organisation-wide links exposing confidential content?
- Do permissions reflect current roles and responsibilities?
- Are inactive sites, accounts and workspaces still accessible?
- Can the organisation identify and remediate oversharing at scale?
The objective is not to make all information inaccessible. It is to ensure that access is deliberate, current and aligned with business need.
Using Microsoft Purview To Classify Sensitive Information
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:
- Clear data owners for sensitive information
- Retention and deletion policies
- Regular access reviews
- Controls for external sharing
- Data loss prevention policies
- User guidance on acceptable AI use
- Testing before wider Copilot deployment
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.
Strengthening Identity And Access Management With Microsoft Entra
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.
Enforcing Least Privilege
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:
- Privileged administrators
- External and guest users
- Service accounts
- Stale accounts
- Users with access to sensitive sites
- Groups with broad or inherited permissions
Reducing standing access limits the potential impact of compromised identities and makes anomalous activity easier to investigate.
Applying Conditional Access
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.
Monitoring AI Activity With Microsoft Sentinel And MXDR
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:
- Unusual access to sensitive data
- Sign-ins from unfamiliar locations or devices
- Sudden changes in user activity
- Repeated access attempts involving restricted information
- Suspicious use of privileged accounts
- Data movement that differs from established behaviour
- Activity associated with compromised identities
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.
Responding To AI-Related Security Incidents
AI adoption should be included in the organisation’s incident response planning.
Relevant scenarios may include:
- A compromised user account querying sensitive information
- Unauthorised use of an AI service to process corporate data
- Prompt injection through connected content
- Accidental disclosure caused by oversharing
- Misuse of privileged access
- Suspected exfiltration of data through an approved AI workflow
Response playbooks should define how the organisation will:
- Confirm the identity, device and activity involved.
- Contain the affected account, session or application.
- Assess which information may have been accessed or disclosed.
- Preserve relevant logs and evidence.
- Notify appropriate legal, privacy, security and business stakeholders.
- Remediate the underlying permission, identity or configuration weakness.
- Review whether regulatory or contractual notification obligations apply.
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.
Moving From AI Adoption To AI Readiness
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:
- Data discovery and classification
- Permission and external-sharing reviews
- Microsoft Purview controls
- Microsoft Entra identity protection
- Conditional Access
- Microsoft Sentinel monitoring
- Incident response playbooks
- User guidance and acceptable-use policies
- Regular testing and maturity measurement
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.
Frequently Asked Questions
Is Microsoft Copilot Compliant With UK GDPR?
Microsoft Copilot is designed to be compliant with UK GDPR by inheriting the privacy, security and compliance commitments of the Microsoft 365 ecosystem. Data processed by the system remains within the UK data boundary for regional tenants and is not used to train foundation models. However, compliance depends on your internal configuration of data residency settings and the correct implementation of Purview to manage personal data retrieval.
Can Microsoft Copilot See My Sensitive HR & Financial Data?
Copilot can only access information that the specific user already has permission to view through Microsoft Graph. If a staff member has access to sensitive HR or financial folders because of legacy permission errors, the AI will retrieve and summarise that data when requested. Securing Microsoft Copilot requires a thorough audit of site permissions and applying sensitivity labels to ensure confidential files remain invisible to the AI engine.
What Is the Difference Between Microsoft Copilot & Microsoft Security Copilot?
Microsoft Copilot is a productivity tool integrated into 365 apps to assist with content creation and data analysis. In contrast, Microsoft Security Copilot is a specialised generative AI tool designed for cybersecurity professionals. It integrates with Defender and Sentinel to accelerate threat hunting, incident response and posture management. Whilst the former helps your team work faster, the latter assists your security operations centre in defending the digital estate.
How Do Sensitivity Labels Affect Microsoft Copilot Responses?
Sensitivity labels act as a primary control mechanism by instructing the AI on how to handle specific documents. When a file is marked with a restrictive label via Microsoft Purview, the system can be configured to prevent the AI from summarising or extracting its content. This ensures that even if a user has access to a document, the AI will respect the governance policy, thereby maintaining the confidentiality of your most sensitive assets.
Do I Need a Microsoft 365 E5 Licence to Secure Copilot?
Whilst you can deploy the technology on E3 licences, an E5 licence provides the advanced tools essential for securing Microsoft Copilot at scale. The E5 suite includes automated sensitivity labelling in Purview, identity protection in Entra ID and comprehensive monitoring via Microsoft Sentinel. These capabilities allow for a more resilient security posture by automating the discovery of sensitive data and providing real time alerts for anomalous AI interactions across the tenant.