Adopt AI without opening new doors for attackers
Frameworks and oversight for how AI is adopted across your organization — risk assessment of AI systems, governance policy, and ongoing accountability, so innovation moves at the pace your business needs.
Your team is already using AI tools, whether there's a policy in place or not. The question is whether anyone's actually looking at what data goes into them.
AI Security Governance is where our cybersecurity consultancy work meets the fastest-moving area of business technology. Staff are pasting client data into chatbots, teams are adopting AI coding assistants and generative tools without a review process, and vendors are quietly adding AI features to platforms your business already relies on. None of that is necessarily a problem — but none of it should be happening unmanaged, either.
We help you understand where AI is actually being used across your organisation, assess the genuine risk each use case carries, and put a governance framework in place that lets your team keep innovating without exposing client data, intellectual property or your compliance position in the process.
Six ways we bring AI adoption under control
From a first exposure assessment to fully embedded governance and staff training.
AI Risk & Exposure Assessments
An honest inventory of where AI tools are already in use across your business, and what risk each one actually carries.
AI Usage Policy & Governance
Clear, enforceable policy covering approved tools, data handling rules and sign-off processes for new AI adoption.
Model & Vendor Risk Review
Due diligence on the AI vendors and models your business relies on, including how they store and use your data.
Data Handling Controls for AI
Practical controls that stop sensitive data leaving your business through an AI tool, without blocking legitimate use.
Employee Guidelines & Training
Plain-language guidance and training so staff understand what's safe to put into an AI tool, and what isn't.
Ongoing Oversight & Audit
Periodic review as new tools and use cases emerge, so governance keeps pace with how AI adoption actually evolves.
How we bring a framework to life
Five stages that move you from unmanaged AI use to a governed, auditable framework.
Map current AI use
We identify which AI tools are actually in use across teams, sanctioned or not, and how data moves through them.
Assess risk
Each use case is assessed for data exposure, vendor risk and regulatory implications specific to your sector.
Draft the governance framework
Policy, approval processes and data handling rules are written to fit how your teams actually work.
Roll out & train
Staff are briefed in plain language, so the policy is understood rather than filed away and ignored.
Monitor & review
The framework is revisited as new tools emerge and your business's use of AI matures.
Why businesses bring us in on AI governance
Risk-led guardrails that let your team keep innovating.
- ✓We assess AI risk the way we assess any other system risk — grounded in your actual data flows, not generic AI hype or fear.
- ✓Our recommendations are designed to let your team keep using AI productively, not to shut adoption down out of caution.
- ✓Because we already handle your infrastructure and security posture, governance for AI slots into a framework we understand, not a bolt-on exercise.
- ✓We keep pace with a fast-moving space, so your policy doesn't quietly go stale six months after it's written.
Industries we support
Before you get in touch
We don't have a formal AI policy yet — is that unusual?
Not at all. Most businesses we work with are in exactly this position: staff have started using AI tools informally, and there's no framework governing what's acceptable.
Will this stop our team from using AI tools?
No — the goal is to make adoption safe, not to block it. Most frameworks we build approve a defined set of tools and clarify what data can and can't be used with them.
Do you assess specific AI vendors and tools?
Yes, as part of the vendor risk review, we look at how specific tools your business is using or considering handle data storage, retention and access.
How does this relate to our existing cybersecurity policies?
AI governance is built as an extension of your existing security framework rather than a separate document, so the two stay consistent.
How often does an AI governance framework need updating?
We recommend a review at least every six months given how quickly new tools and features emerge, with ad-hoc reviews when a major new tool is adopted.
Ready to see where your AI exposure actually sits?
Start with an exposure assessment, and we'll show you exactly where the risk is before we talk about policy.