Ask an AI browser to do something simple — summarize important emails, buy a pair of running shoes, or rebuild your tab pile — and you’ll get a revealing answer: sometimes it can, sometimes it will stall, and often it will ask for help.
The past few months have seen a flood of so-called agentic browsers: OpenAI’s Atlas, Perplexity’s Comet, The Browser Company’s Dia, plus chat-powered add-ons in Chrome and Edge. CEOs and marketers sell them as digital coworkers. Reporters and security experts are finding something messier: a set of powerful ideas hamstrung by slow performance, brittle prompts, and eye‑watering security gaps.
Where the promise came from
The pitch is seductive. Instead of opening tabs, copying text and toggling accounts, you tell a browser what you want and—supposedly—let it finish the job. Entrepreneur’s recent piece showed the upbeat case: solopreneurs are already using Atlas to draft content, audit landing pages, kill tab chaos and even perform inline edits without copy‑paste. For some freelancers and founders, that can translate into reclaimed hours and cleaner workflows.
That optimism isn’t wrong. In narrow, carefully tuned tasks an agentic browser can speed things up. The friction it eliminates matters: stitching research, composing drafts and comparing products are tedious. The plain truth is that those wins are situational; they depend on good prompts, predictable websites and careful supervision.
Where reality trips over the dream
Independent testing tells a different story. Reporters who pushed five different AI browsers through real tasks found a recurring pattern: they’re often slow, error‑prone and demand you to become a better prompt engineer just to get basic results. An inbox summarization that should take a minute can end in false positives, missed context, or pages of irrelevant output unless the user writes a very specific, awkward prompt.
Shopping is another illustrative failure mode. The browsers can research quickly but misread basic attributes like color or size. Atlas has been observed nagging users repeatedly to confirm cart contents, and at times it spent long stretches simply trying to close windows. In short: the tools still require oversight. They’re helpers that want a babysitter.
The security problem you should be worried about
This is where the stakes rise from annoying to dangerous. Agentic browsers must act on your behalf to be useful: they need session cookies, saved credentials, maybe your payment info. That level of access creates a huge attack surface.
Researchers have demonstrated prompt‑injection attacks where benign‑looking web content tricks an AI into leaking data or performing actions it shouldn’t. Tests have shown Comet could be manipulated into revealing bank-related information, and feeding Atlas crafted URLs reportedly coaxed it into visiting a linked Google Drive and deleting files. Those aren’t theoretical edge cases — they exploit the exact privileges that make agentic browsers attractive.
Security teams see an additional blind spot: traditional network logs often miss what happens inside a browser session. When an autonomous agent clicks a button, fills a form and sends a request within an authenticated session, the cloud sees legitimate traffic. The danger is the “session gap”: local actions that look like the user did them, but were triggered by a compromised agent.
How enterprises (and cautious users) can respond
For organizations, the advice is blunt: don’t treat these as ordinary browsers. Security leaders should discover any shadow AI clients on endpoints, restrict agentic browsers from sensitive applications, and layer additional browser protections. Blocking or allow‑listing access to HR portals, code repositories and finance systems until the platforms prove themselves is prudent.
Practical steps for everyday users include limiting saved credentials, keeping payment methods off autofill where possible, and treating any auto‑action from a browser as suspect until you’ve confirmed it. These steps reduce convenience but they also reduce the most straightforward attack vectors.
The use case gap
There’s a middle lane where AI browsers already help: predictable, repetitive workflows with clearly structured outputs. Content creators, solo founders and researchers can lean on them to gather and format information, draft documents, or rebuild a messy tab state — provided they accept that the browser won’t be fully autonomous. For anything involving money, legal forms, or sensitive data, human confirmation remains nonnegotiable.
If you want to see the wider industry context, agents are showing up in places like Chrome’s new AI mode that can book appointments and manage tasks, which raises similar questions about automation and privilege (Google’s AI Mode Adds Agentic Booking). Google and others are also deepening integrations between AI models and user data — for example, systems that can search your Gmail and Drive for context — which complicates how privacy and productivity collide (Gemini’s Deep Research May Soon Search Your Gmail and Drive). For users running lots of AI features on Windows, there are already guides about how to quiet unwanted AI assistants and ads if you prefer less automation in your day (clean-up-windows-11-25h2).
So what does this mean going forward?
Agentic browsers are a work in progress: compelling in concept, uneven in execution, risky if trusted too far. The next meaningful advances won’t come from flashier demos but from two places at once — reliability improvements that let the AI reason about interfaces and context, and security designs that curb the privileges agents need or that more visibly separate their actions from your authenticated session.
Until then, treat these browsers like powerful tools that require direction. They can take a lot off your plate, but they need someone watching the pot. That someone is still almost always you.