AI Browsers Are Here. Is Your Security Team Ready?

With artificial intelligence tools positioned to redefine the web browser experience, organizational leaders must ask themselves a tough question: Are we prepared for the inevitable security risks?

They can’t afford to put off this discussion because AI browsers are already gaining notable traction. True, Google Chrome still dominates with nearly three-quarters of the market share and as many as 3.62 billion users. But OpenAI has introduced its own web browser, Atlas on Apple laptops, with plans to make it available on Microsoft’s Windows, Apple’s iOS phone operating system and Google’s Android phone system. In addition, Perplexity AI is making its own web browser, Comet, available worldwide and free to users.

This is about more than introducing new AI options in what has been a relatively settled technology space. It’s about a fundamental transformation in which AI no longer serves as a separate add-on to the browsing experience. Now, it is the browsing experience, and it promises to increase productivity for users while personalizing their interactions and automating tasks.

Instead of merely acting as an interface for humans/employees as they search and surf online, which is how traditional browsers essentially work, AI goes several steps beyond by taking action on the users’ behalf in a proactive, interactive manner. Although the technology’s capabilities are still quickly evolving, it can recall what you did before online and pick up where you left off and make recommendations to you based upon contextual retention/knowledge. It will autonomously click around the internet for you. Or it will take the initiative to book your appointments, pay an invoice, evaluate a vendor, write a proposal, fill out a time sheet or purchase Taylor Swift’s latest album.

This shift expands the attack surface dramatically, as any system that can act autonomously, retain context and access sensitive services, becomes a high-value target for manipulation, abuse or unintended actions triggered by untrusted content.

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Increasing the Stakes of Shadow AI

To take the technology even further, AI browsers will combine all of the information collected along the way to build a detailed, proprietary profile of individual employees and – most critically – identify how these profiles fit into their organizational context. This creates security risk when that accumulated context is applied outside its original scope. 

For example, a user might ask the AI browser to summarize an internal dashboard showing quarterly sales performance. If the browser has already inferred the user’s role, region or customer portfolio from prior activity, the summary could unintentionally include sensitive insights, comparisons or trends that exceed what was explicitly requested or be sent to a remote AI service as part of the processing. In the worst scenario, this same contextual awareness could be exploited by malicious content to prompt the agent to extract or reframe internal data in ways that violate data-handling or access policies.

Keep in mind that AI will be present on any webpage, including enterprise-linked and heavily fortified cloud products such as financial applications. Amazon has already sued Perplexity AI, claiming that its agentic shopping feature covertly accessed Amazon’s customer accounts and disguised automated activity as human browsing.

This level of immersed integration profoundly extends the potential pitfalls of shadow AI, in which employees use these tools without the approval or oversight of the IT department. In more typical cases, managers minimize the risks of shadow AI as they train teams about the inherent security issues and coach them away from problematic usage.

AI browsers, however, represent a trickier form of shadow AI. They’re empowered agents, taking control of the mouse and eyes on every page, so they can proceed to work unchecked on sensitive internal systems regardless of security policies. All this happens in a way that traditional data loss prevention (DLP) controls cannot detect. 

DLP controls are designed to stop files from leaving the network or keep suspect strings from getting pasted into a generative AI app. AI browsers therefore introduce intrinsic weaknesses to the network because they allow the browser to access – read, write and delete – data without explicit user consent.

Privacy Concerns for Personal Routines

AI browsers operate with a level of insight into user activity that goes far beyond what a traditional browser can see. Because the AI layer analyzes browsing behavior to tailor responses, it inevitably gains awareness of whatever appears on the screen: personal accounts, work material, financial pages or anything else a user views as part of their daily routine. Instead of the old model where browsers collected data only at specific moments, AI browsers function as continuous observers. Each action of opening a site, submitting a prompt or delegating a task contributes to an evolving profile of habits and intentions.

Although Atlas offers privacy settings to disable memories or clear stored information, these controls operate only on the explicit data entries. The conclusions the system has already drawn from those entries can remain intact because undoing inferences presents a greater challenge than merely reversing raw facts.

What emerges is a fused system: the detail-level view of a browser combined with an AI capable of interpreting and connecting those details. This pairing allows the assistant to anticipate needs and offer helpful suggestions. This also implies the AI constantly absorbs information regarding personal routines and preferences.

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3 Steps Toward Protected AI Browsing

As indicated, senior leaders must start preparing to safeguard their organizations from AI browser-created vulnerabilities now, not later. Here are three steps to consider in responding to the challenge.

Have the Right Controls in Place

Move beyond a purely network-centric model to one that prioritizes user behavior, endpoints and interactions within AI browsers themselves. This involves the implementation of solutions that enable browser activity analysis and endpoint DLP, while requiring all AI browser usage to pass through a vetted, enterprise-grade AI gateway to act as a centralized “AI cop” that eliminates troublesome activity.

Resist Reactionary Blocks

No one likes to deal with a “Department of No” security team. So, include employee input in developing AI browser policies to ensure safe usage while avoiding user frustrations and precarious policy workarounds.

Consider Enterprise Browsers

Enterprise browsers are specifically designated for organizations, with greater IT oversight over web access and activity. They mitigate risk by restricting users to only certain categories of data via a secure browser.

Like any other innovation with perceived superpowers, AI browsers are poised to redefine the possibilities of our daily usage of technology. Organizational leaders can’t really stop them entirely.

But they can contain employee usage within mutually acceptable limitations by investing in browser activity analysis, endpoint DLP, enterprise-grade AI gateways and/or even enterprise browsers — while working as collaborators with staffers on policies instead of taskmasters. With this, they will ensure that the next, big thing in AI remains in its place as a helpful work assistant, rather than a risk-generating burden.