AI Security
Governing how your business builds, deploys, and uses AI — so productivity gains don't come at the cost of your data walking out the door through a chat window.
Your data policy didn't account for AI. It needs to.
Generative AI tools moved into the workplace faster than most security teams could write a policy for them. Employees paste customer data, contracts, and source code into public AI assistants every day — not out of malice, but because it's the fastest way to get something done.
At the same time, AI is showing up inside your existing systems: copilots in productivity suites, AI features bolted onto SaaS tools you already pay for, and increasingly, AI agents that can take action on your business systems rather than just answer questions. Each of these is a new way for data to move, and a new thing that needs a policy.
What AI security actually covers
- Visibility into which AI and generative AI tools are actually in use across your organization — most security teams are working from an incomplete list.
- Policy that governs what data can be shared with which AI tools, enforced at the point of use rather than after the fact.
- Governance over AI systems your own teams build or deploy — who owns them, what they can access, and how that access is reviewed.
- Monitoring for unusual access patterns where AI tools or agents touch sensitive systems.
How we approach it
We don't treat AI security as a brand-new program bolted onto your stack. For most clients, it's an extension of controls you already have — the cloud security and data-loss prevention policies we implement can be extended to cover generative AI applications, the same way they already cover cloud storage and email.
We start by finding out what's actually being used today, because policy without visibility is just a document nobody follows.
You may have a gap here if…
- Nobody in your security team can name the AI tools your employees use day to day.
- There's no written policy on what data can or can't go into an AI assistant.
- An AI tool or copilot has access to business systems that nobody formally reviewed.
- Your last data-handling policy was written before generative AI was part of daily work.
Not sure where you stand on this?
Run the free regulatory assessment, or talk to the team that implements this for a living.
The other six domains.
Perimeter Controls
Threat recognition, surveillance, and pattern analysis at the edge of your network — before anything reaches what you're actually trying to protect.
Read more →Network Controls (Cloud)
Reducing the blast radius of any single compromised connection — on-prem or in the cloud — by governing access through identity and policy, not network location.
Read more →Endpoint Controls
Securing every laptop, phone, and server your people actually use — because this is usually where the real damage happens, not at the network edge.
Read more →Data Controls
Stopping sensitive data from leaving the places it's allowed to be — whether it's trying to leave through email, a cloud upload, a USB drive, or a chat window.
Read more →Governance Controls
The policy and accountability layer that ties every other control back to what your business and your regulator actually require.
Read more →Industrial Controls
Securing the systems and processes behind physical operations — the equipment, sensors, and control systems that keep a manufacturing line or physical operation running.
Read more →