AI security for UK organisations: see and control how your people use AI

What is AI security?

AI security covers two related jobs. The first, and the one most UK organisations face today, is securing how employees use AI: chat assistants in the browser, AI features inside the SaaS apps you already pay for, desktop AI apps, browser extensions, coding assistants and, increasingly, AI agents that take actions on someone's behalf. The second is securing the AI applications and agents you build or deploy yourself, so they cannot be manipulated into leaking data or doing something harmful.

Both are about the same underlying questions:

• Which AI tools and agents are in use, and who approved them?
• What data is going into them, and where does it end up?
• What can they do with the access they have been given?
• Can you show a client, an auditor or the ICO that AI use is under control?

This site focuses on the first job, because that is where most organisations start, and on the Check Point products that address it. If you want a vendor-neutral overview of generative AI security and the wider market, our sister site cloud-security.cloud covers it.

The main AI security risks

We cover each of these in depth in our guide to AI security risks, but in short:

• Shadow AI: staff sign up to AI tools with personal accounts, so company data sits in services whose terms, storage and security nobody has checked. See what is shadow AI.
• Sensitive data in prompts and uploads: client records, contracts, credentials, source code and financial data pasted into a chat or uploaded as a file. See AI data leakage.
• Oversharing in approved assistants: tools such as Microsoft Copilot can surface any content a user has permission to see, so weak file permissions become visible quickly. See Microsoft Copilot security.
• Prompt injection: hidden instructions in a web page, document or email that steer an AI tool into leaking data or taking actions. See prompt injection.
• Agents, coding assistants and MCP: tools that connect to company systems and act with real permissions, often installed by a single user. See MCP security and AI coding assistant security.

Most of these are data protection problems first, which is why AI security sits so closely with UK GDPR.

Check Point Workforce AI Security: discover, govern, protect

Check Point Workforce AI Security is Check Point's product for securing employee use of AI. Check Point describes it as a way to "discover, govern, and protect employee AI usage across browser, desktop, and agents". In practice that means:

• Discover: an inventory of the AI apps, tools, browser extensions, code assistants, agents and MCP connections in use, sanctioned or shadow, with an AI application catalogue, risk scoring, adoption trends and session-level visibility
• Assess: understanding AI risk relative to your own security and compliance requirements, helped by AI-powered analysis that sorts prompts into use-case categories such as Marketing, Debugging and Legal
• Govern: per-app policies covering who can use what, copy and paste, sensitive data in prompts, files and agent actions, with audit trails and reports
• Protect: contextual, AI-powered data loss prevention that can redact personal data, credentials, source code and financial data from prompts, uploads, files and images (with OCR), warn or guide the user, or block the action

Check Point names the public AI tools it covers as ChatGPT, Gemini, Claude and Copilot, alongside AI features inside SaaS apps, browser extensions, code assistants such as GitHub Copilot and Cursor, and MCP-connected workflows. It deploys as a lightweight browser extension, with a desktop agent available for AI used outside the browser. If you already run Check Point firewalls, Check Point says its AI Network Firewall can deliver Workforce AI capabilities from the firewall itself, with no agent or extension to install. Our deep dive explains how Workforce AI Security works, stage by stage.

Essentials or Enterprise?

Workforce AI Security comes in two tiers. Check Point's own descriptions in its administration guide are short, and we stick to them:

Read more on Workforce AI Security Essentials, Workforce AI Security Enterprise and the side-by-side Essentials vs Enterprise guide. Our Workforce AI Security pricing page explains how licensing works; for figures, ask us for a quote. Feature details change as Check Point develops the product, so we confirm entitlements when we quote.

Already a Check Point customer using GenAI Protect? Check Point says Workforce AI Security replaces it and is now its primary offering for employee AI security; our GenAI Protect end of sale guide explains what that means for you.

Policy, governance and UK regulation

Technology enforces rules; it does not write them. Most organisations need a short set of documents and decisions before, or alongside, any tool:

• An AI acceptable use policy that tells staff which tools they may use and what data must stay out of them, with a template to start from
• An AI security policy for the security side: inventory, access, logging, agent approval and incident response
• An AI governance framework that sets ownership and review, and an AI risk assessment approach for each tool
• An understanding of AI and UK GDPR, including when you need an AI DPIA, what the ICO's AI guidance expects, and whether the EU AI Act applies to UK businesses like yours

Workforce AI Security supports all of this with evidence: which tools are used, by whom, for what, and what was redacted or blocked. These pages are general information, not legal advice. For staff training, our sister site covers safe use of AI training.

Beyond employee use: AI apps and agents you build

If your organisation builds its own AI applications or deploys AI agents on cloud and low-code platforms, the risks move from what staff type to what the application or agent can be tricked into doing. Check Point groups its products for this under its AI Security pillar, covered on our Check Point AI Security page:

• Check Point AI Agent Security: identifying agents built on supported cloud and low-code platforms, assessing their risk, allowing or denying the tools and MCP servers they use, and detecting prompt attacks at runtime, drawing on Lakera, the AI security company Check Point acquired
• Check Point AI Red Teaming: automated adversarial testing of models, live applications and agent endpoints, re-run after model, prompt or capability changes
• Check Point AI Network Firewall: AI visibility, governance and protection from existing Check Point firewalls, including inline protection for AI applications against prompt injection and data exfiltration

For most organisations, though, employee use is the place to start, and Workforce AI Security is the product for it.

How Forever Systems helps

We keep the first step small and useful, and build from there:

1. Discovery first. We can start with a pilot group so you can see which AI tools, extensions and agents are really in use before anyone writes rules.
2. Policy you can enforce. We help you decide what to approve, restrict or block, and turn your AI acceptable use policy into Workforce AI Security policies.
3. Choose the right tier. We look at whether your AI use is browser-based (Essentials) or includes desktop apps, coding assistants and agents (Enterprise), and quote for what you need.
4. Roll out in stages. We help you move from monitoring to warning, redaction and blocking at a pace your people can absorb, and help you review the results.

Pricing depends on the number of users, the tier and the term, so ask us for a quote. To talk about AI security in your organisation, contact us.