Generative AI has become the fastest-adopted technology in enterprise history. In 2024, AI tool usage nearly doubled in just six months, with 75% of global knowledge workers now using AI in their daily work.

Over the past year, we’ve seen a growing maturity in how enterprises approach generative AI. What started as a scramble to block ChatGPT or “allow it for marketing only” has evolved into AI committees, usage guidelines, and formal policies. That’s progress. But it’s also only the beginning.

The reality we are hearing from security teams is clear: while most organizations have discussed AI and defined policies, very few have the controls to actually enforce them. In most cases, what exists is not a true policy but a memo. The result is a growing gap between intention and implementation, which is where the risk lives.

The First Challenge: Visibility

The most immediate challenge is that traditional security tools aren’t built for how AI tools work. AI usage doesn’t look like legacy SaaS. It’s not tied to managed apps, defined APIs, or straightforward access flows. It’s dynamic, fast-changing, and increasingly embedded into browser and web applications.

AI is being used:

• Directly in browser-based tools like ChatGPT, Claude, Gemini, and Copilot
• Through extensions that add AI into Gmail, Docs, or Salesforce
• Embedded into SaaS platforms, quietly introduced via product-led growth

It’s not just major platforms like ChatGPT. Thousands of third-party AI integrations—browser extensions, SaaS platforms, and APIs—quietly embed AI into daily workflows. In our recent State of Browser Security report, we noted that the Chrome Web Store has over 1,400 extensions with “ChatGPT” in the name. The top 20 extensions alone have over 1 million users each.

Most network and endpoint tools don’t see this. CASBs and SWGs rely on third-party app feeds or domain-level allow/block lists—controls that were never designed for the velocity of today’s AI landscape. New generative AI tools, extensions, and integrations are being published daily. By the time a threat feed updates or a tool is classified, your employees may have already adopted it.

You can’t enforce a policy on something you can’t see.

The Second Challenge: Policies Exist, but Controls Do Not

Many organizations have taken meaningful steps in developing AI policies. These often include more than just a list of approved tools. They define acceptable use cases, outline data sensitivity thresholds, and provide guidance on how employees should interact with AI responsibly. The problem is not the lack of direction. It is the lack of enforcement.

Most security teams do not have the visibility or control required to act on those policies. Two employees might use the same AI tool. One uses it to refine a sales email. The other uploads a confidential roadmap. Both actions happen in the same interface, but only one crosses a line. Without visibility into what was typed, pasted, or uploaded, there is no way to enforce the difference.

This is why browser-level context is essential. The browser is where prompts are written, where files are uploaded, and where sensitive information is often shared. It is also the only place where security teams can inspect those interactions in real time, before any data leaves the organization.

Where AI Governance Needs to Go

An effective AI policy does more than define acceptable use. It creates the conditions to enforce it. That requires moving beyond static controls and investing in visibility and enforcement that match how AI is used today. This is not just about checking a box for compliance. It is about protecting sensitive data, minimizing the risk of intellectual property exposure, and maintaining trust in a fast-moving regulatory environment. 

Why the Browser Is the Logical Control Point

With employees spending 85–90% of their time in the browser, and AI tools being primarily browser-based, the browser has become the new endpoint. It’s also a key data layer, where input meets output, and user behavior drives outcomes.

Browser-focused controls offer several advantages over legacy network or endpoint solutions:

• Granular data visibility: Inspect applications, prompts, uploads, inputs, and extensions in real time
• Dynamic policy enforcement: Block or redact sensitive data before it’s shared
• User context awareness: Track session identity, domain, and behavior patterns
• Frictionless deployment: No need to replace browsers; can work across environments

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As organizations mature their AI strategy, investing in the browser as a control point is the natural next step—especially for those who’ve already deployed EDR, email security, and SWG.

The Next Phase of AI Governance

If 2024 was dominated by committee formations and policy creation, 2025 must focus on implementation and enforcement. Effective AI governance requires a continuous approach rather than a one-time effort, adapting to context rather than remaining static, and seamlessly integrating into daily workflows instead of being added as an afterthought. 

Traditional security tools like firewalls and email filters fall short in meeting these requirements, but browser-focused controls can provide the necessary oversight where AI interactions actually occur. You've already accomplished the challenging task of establishing governance frameworks—now it's time to enforce those rules directly within your employees' primary workspace.

Interested in learning more about Keep Aware assists with enforcing AI policies? Schedule a demo with one of our team members to take control of AI usage in your organization.