Friday 11th September 2026
The biggest AI security risk isn't the model. It's the data you've already forgotten about.
Most AI security discussions focus on models, prompts, governance and acceptable-use policies. But many security teams are missing a more fundamental issue:
What can your AI actually access today?
Whether it's Microsoft Copilot, ChatGPT Enterprise, Gemini, GitHub Copilot, security copilots or autonomous AI agents, every AI capability relies on access to data.
That's where the challenge begins.
For years, security teams have concentrated on controlling which users can access sensitive information. Now they also need to understand what AI can access, analyse and surface.
And for many organisations, the answer isn't clear.
Not because they lack security tools.
Not because they lack policies.
But because they lack visibility into their data estate.
Security teams have been dealing with excessive permissions for years:
Historically, these represented potential risk. AI changes the equation.
Research from Cyera found employees actively use only around 4% of the permissions granted to them, leaving the vast majority unused.
AI doesn't ignore those permissions.
It inherits them. An AI assistant won't recognise that a repository is overshared or that a user should no longer have access. It simply operates within the permissions it has been given.
At machine speed.
Across thousands of files.
What was once an access governance issue can quickly become a data exposure issue.
Most organisations can answer:
Far fewer can answer:
Exactly which sensitive data can AI tools, copilots and agents access today?
To answer that, security teams need visibility into four areas:
What data exists? Across Microsoft 365, SharePoint, OneDrive, Teams, Exchange, Azure, AWS, SaaS applications and legacy repositories.
What data is sensitive? Customer data, intellectual property, source code, financial records, employee information and regulated data.
Who or what can access it? Users, service accounts, applications, AI assistants and autonomous agents.
What's actually happening? Which AI tools are accessing data, indexing repositories, handling sensitive content and operating autonomously.
Without that context, securing AI becomes guesswork.
Most organisations already have security controls in place:
The issue isn't usually a lack of tooling. It's a lack of visibility across them.
One platform understands data. Another understands identities.
Another monitors activity.
Meanwhile the risk sits between all three.
AI amplifies these blind spots.
Before you can govern AI, you need to understand:
This is why Data Security Posture Management (DSPM) is becoming a critical capability for AI security.
Not because it secures AI directly.
Because it gives security teams the visibility needed to secure the data behind it.
You can't govern what you can't see.
And you can't secure AI if you don't understand the data it's already connected to.
Understand What Your AI Can See
The Bytes & Cyera Data & AI Assessment helps security teams identify:
Request your Data & AI Assessment here and discover what your AI can already see.
Want to keep informed? Sign up to our Newsletter