The AI Security Gap No One Planned For

We are living through one of the fastest technology shifts in history. In the past, adopting new tech was a top-down decision—IT vetted it, procurement bought it, and security secured it. AI is different. It’s bottom-up.

Your marketing team is using it to write copy. Your developers are using it to debug code. Your HR team is using it to summarize resumes. And in most cases, they didn’t ask for permission—they just signed up and started working.

This speed is great for innovation, but it has created a massive blind spot. While organizations race to integrate these tools, they are often sprinting right past governance, creating Shadow AI Risks that most security teams aren't even seeing, let alone managing.

When Innovation Outpaces Governance

The fundamental problem isn't the technology itself; it's the pace of adoption. AI is shipping faster than security policies can be written.

In a traditional software cycle, you have checks and balances. With AI, a developer can paste proprietary code into a public LLM (Large Language Model) to get a quick fix, or an executive can upload a sensitive strategy document to a chatbot to get a summary.

The data has left your secure perimeter before you even knew it was at risk. The "perimeter" is no longer just your firewall; it’s now defined by the terms of service of a dozen different AI startups that your employees are using on their personal accounts.

The Reality of Shadow AI Risks

We used to worry about "Shadow IT"—unapproved software installed on company laptops. Shadow AI is that problem on steroids.

Because AI tools are often browser-based and free (or cheap), they are invisible to traditional endpoint detection. Employees aren't trying to be malicious; they are trying to be efficient. But this efficiency comes with significant Shadow AI Risks.

When proprietary data is fed into public models, where does it go? Is it being used to train the next version of the model? If a third-party AI tool gets breached, is your data exposed? Without visibility into who is using what, you can’t answer these questions. You are effectively outsourcing your data security to companies you’ve never vetted.

The Ownership Void: Who Secures the AI?

One of the biggest reasons this gap exists is a lack of clear ownership.

• Is AI security the CISO’s job?

• Is it the CTO’s job because it involves code?

• Is it Legal’s job because of copyright and privacy issues?

When everyone owns a piece of the problem, no one owns the solution. This ownership void leaves massive cracks in the defense. Policies remain unwritten because no single department feels empowered to enforce them. Meanwhile, usage continues to skyrocket, widening the gap between what you think is happening on your network and what is actually happening.

"Compliance is Asking, Engineering is Guessing"

Eventually, an auditor, a board member, or a key customer is going to ask: "How are we ensuring our data isn't leaking through AI tools?"

Right now, in too many organizations, compliance is asking that question, and engineering is guessing the answer.

Compliance teams are drafting policies that say "Don't use unapproved AI," but they have no way to verify if those policies are being followed. Engineering teams are under pressure to ship faster, so they use the best tools available, assuming that "someone else" checked the security implications.

This disconnect is dangerous. You cannot build a defensible security posture on guesswork. You need to move from "hoping employees follow the handbook" to actively validating which tools are touching your data.

Closing the Gap

The solution isn't to ban AI. That’s a losing battle that stifles innovation. The solution is to bring AI out of the shadows.

You need to establish clear visibility. You need to know which APIs your applications call and which external services your teams use. Just like we discussed with general cyber risk, you cannot secure what you cannot see. Check out one of our past blogs on AI-Powered Cyberattacks.

Identifying Shadow AI Risks isn't about punishing employees for trying to work faster; it's about building a guardrail that allows them to run fast without running off a cliff.

Don't Let AI Be Your Blind Spot

AI is changing the landscape every day. If you are ready to stop guessing and start validating your true exposure—from traditional vulnerabilities to the new world of AI risks—we can help you see the full picture.
Schedule a demo with Red Sentry to see how we help you secure your assets in the age of AI.