How to Secure AI in Your Business: A Practical Guide

Governance before technology

The most common mistake businesses make when approaching AI security is starting with the technology and working backwards to the governance. The right sequence is the opposite: establish what controlled AI use looks like for your organisation, then configure the technology to enforce it.

This guide is structured in the order you should approach it. Each step builds on the previous one.

Step 1: Establish your AI use policy

Before configuring anything, your organisation needs a clear, written position on AI use. It needs to answer the following questions:

• Which AI tools are approved for use at work, and which are not?
• What categories of data must never be entered into any AI tool?
• What categories of data may be used with approved tools under what conditions?
• Who is responsible for AI governance within the organisation?
• What is the process for approving new AI tools for business use?

The prohibited data categories are the most important part. At minimum, these should include personally identifiable information about clients or staff, financial account details, legally privileged material, information covered by NDAs, and anything classified as sensitive personal data under UK GDPR Schedule 1.

For businesses holding ISO 27001, the AI use policy slots into the existing ISMS framework under Annex A.8 (technological controls) and A.5 (organisational controls). For Cyber Essentials holders, it reinforces the user access and software controls that the scheme requires.

Step 2: Audit your current AI exposure

Before you can control AI use, you need to understand what is currently happening. In most organisations, this audit produces uncomfortable findings: staff are using a wider range of AI tools than management is aware of, and the data being entered includes categories that should be restricted.

The audit should cover:

• Review of web proxy or DNS filtering logs for AI tool domains (ChatGPT, Gemini, Claude.ai, Grok, Perplexity and others)
• Review of browser extension installs across managed endpoints
• Staff survey or structured interviews to understand current AI tool usage and use cases
• Review of any AI integrations built into existing SaaS applications

Step 3: Configure your approved AI environment

For most UK SMEs using Microsoft 365, the approved AI environment is Microsoft 365 Copilot. The following configuration steps are required before Copilot can be considered securely deployed.

SharePoint Restricted Search limits Copilot to a curated set of approved content, preventing unintended data surfacing in environments where permissions have not been tightly managed.

Microsoft Purview sensitivity labels classify your data: Public, Internal, Confidential, Highly Confidential. When labels are applied across your tenant, Copilot respects them. Label deployment requires a taxonomy decision, a deployment plan, and user training.

Data loss prevention policies need to be reviewed and updated to cover AI workloads: specifically to prevent sensitive data classifications from being included in Copilot outputs shared externally, and to ensure AI-generated content inherits appropriate labels.

Conditional Access policies should be reviewed to ensure that Copilot access requires multi-factor authentication as a minimum. For higher-sensitivity environments, Compliant Device requirements should be enforced.

Audit logging must be enabled and verified. Copilot activity is logged in the Microsoft Purview compliance portal. Verify it is enabled and that logs are retained for a period appropriate to your compliance obligations.

Step 4: Control unapproved AI tools

Approving Copilot is the positive side of the governance framework. The other side is controlling access to tools that have not been approved:

• DNS filtering or web proxy blocking for known consumer AI tool domains – effective for managed devices on the corporate network
• Microsoft Defender for Endpoint application control – can restrict browser-based access to AI tools on managed endpoints
• Microsoft Entra ID Conditional Access with Compliant Device requirement – prevents unmanaged devices from accessing corporate Microsoft 365 data
• Browser extension management via Intune or Group Policy – restrict installation of unapproved AI browser extensions

No technical control is absolute. This is why the policy and culture element remains important alongside the technical controls.

Step 5: Train your staff

Technical controls without staff understanding create friction without safety. AI security awareness training should cover what tools are approved and how to access them, what data must never be entered into any AI tool with concrete role-specific examples, how to recognise AI-enhanced phishing and social engineering attempts, and what to do if they are unsure whether a specific AI use is appropriate.

Step 6: Monitor, review and iterate

AI security governance is not a one-time project. Establish a quarterly review cycle that covers usage data from Microsoft Purview, policy review against current business practice, threat landscape updates, and new Copilot feature releases that may create new governance considerations.

How System Force IT can help

The steps above describe a complete AI security programme. For most SMEs, delivering it without specialist help is a significant undertaking. System Force IT manages the technical configuration, policy framework, staff training and ongoing review for clients across Gloucestershire and the South West.

Our AI Readiness Assessment is the starting point: it assesses your current position across all the dimensions above, identifies the gaps, and produces a prioritised remediation roadmap at a fixed price.

Contact System Force IT to discuss your AI security programme.