When Gemini 3 is capable of automatically browsing the web, comparing prices, and placing orders, the browser transcends its traditional role as a mere gateway and evolves into an execution layer. The true impact may not be felt by AI peers but rather by a plethora of utility apps.

Written by/Haiyue

Edited by/Zhuyu

Over the past two years, the prevailing narrative surrounding AI products has centered on their increasing 'intelligence': larger parameter sets, enhanced multimodal capabilities, and improved proficiency in writing and drawing. Yet, users often perceive these advancements as merely making AI 'better at chatting,' still falling short of being 'more capable of accomplishing tasks.' Consequently, the market has begun to pose a more specific query: Where should AI be positioned to transition it from a mere 'feature' to an integral 'habit'? The answer increasingly points towards the browser.

The rationale is straightforward. The browser serves as humanity's default workspace for online activities: upon opening it, one encounters a stream of information, shopping options, forms, ticket booking services, reimbursement processes, documents, emails, and calendars all in one place. Whoever gains control over the browser is one step closer to 'doing everything on behalf of the user.' Perplexity took the lead with Comet, and OpenAI followed suit with Atlas, both betting on the same premise: the future of interaction lies not in opening specific apps but in entrusting a sentence to an intelligent agent capable of navigating web pages.

When Google takes action at this juncture, its significance extends beyond merely 'following suit' and instead involves 'rewriting the distribution landscape.' Chrome's strength does not lie in the stunning nature of its model but rather in its seamless integration of AI as a default setting: a permanent sidebar, visible webpage context, and a utilizable account system.

Thus, AI no longer necessitates users to 'remember it'; it is omnipresent every time a user opens a tab. A similar logic has already been validated in another domain: while the stage can propel new entities into the spotlight, their true potential is determined by their ability to perform consistently in real-world scenarios.

The gateway is not merely about location; it's about 'permission'

Integrating Gemini into Chrome's sidebar may initially appear as a mere product form upgrade: reducing the need for copying and pasting, minimizing page jumps, and providing a more always-on assistant. What truly packs a punch is its transformation of the 'gateway' from a mere traffic conduit to one capable of retrieving information across applications. Thus, the gateway's role shifts from 'directing users somewhere' to 'empowering someone to act on behalf of the user.'

The most groundbreaking aspect of this update is 'Auto Browse.' It transcends merely summarizing web pages or assisting with price comparisons; it embarks on multi-step workflows: finding flights and hotels, selecting dates, comparing prices, and adding suitable options to an itinerary; or navigating through tedious processes like reimbursement, subscription management, appointments, and material collection on web pages.

More critically, it performs these 'operations' on a user-visible interface: AI does not generate answers in the background but completes processes in the foreground. For users, this fosters a new trust structure: not 'it sounds authentic' but 'it truly gets things done.'

Google has also advanced the 'Connected Apps' system: services like Gmail, Calendar, Maps, Flights, and Shopping already constitute Google's strongholds. Now, AI can directly invoke them after authorization, transforming the pain point of 'cross-site jumps' into a process cost that can be absorbed. For instance, in travel planning, the traditional approach involves users jumping back and forth among dozens of tabs; now, it's more akin to AI shuttling among tabs, with users only responsible for confirming key nodes.

Externally, this is perceived as an experience upgrade; internally, it's about the platform regaining control over task distribution: in the past, tasks were distributed to apps; in the future, they will be distributed to agents. The account system and ecosystem behind the agent determine its reach.

This shift in 'permission-based gateways' will directly diminish the space for two types of products. The first is utility apps: price comparison tools, coupon collectors, form assistants, screenshot translators, simple photo editors, and itinerary organizers—these functions once relied on single-point experiences for survival. Once the browser sidebar becomes a permanent fixture and can complete tasks directly within web pages, users' motivation to open standalone apps will significantly decline.

By integrating web-based image editing tools like 'Nano Banana' into the sidebar, Google is essentially leveraging the browser to consume scenarios for lightweight creation and processing tools.

The second type is content distribution platforms: as users become more accustomed to 'entrusting problems to agents and letting them navigate web pages,' the value of content platforms will be re-evaluated. Because agents naturally tend to 'compress information into conclusions and turn processes into steps.' This enhances efficiency for users but alters the traffic structure for platforms: shifting from 'people clicking on pages' to 'agents reading pages.'

Whoever can be better understood, quoted, and executed by agents (e.g., by providing structured data, callable process standards) will be more likely to maintain a presence in the new distribution chain. Google's mention of open protocols (such as standardized attempts to streamline the shopping process) also paves the way in this direction: making it easier for agents to complete transaction closures.

The real competitors of browser agents are not Comet and Atlas but 'accident rates'

Viewing this round of competition merely as 'Google vs. OpenAI vs. Perplexity' risks misjudging the focus. The true challenge for browser agents lies not in whether the model can write or see but in whether it dares to act, whether its actions will cause problems, and who is responsible if they do. In other words, what determines its scalability is not demo videos but accident rates and controllability.

From a product design perspective, Google has already deliberately set risk boundaries: sensitive operations like payments and posting updates must be paused for user confirmation; Auto Browse currently also comes with subscription thresholds and regional restrictions, testing the waters within controllable ranges. Wired also highlights security risks like prompt injection: when agents can click, fill out forms, and log in, web pages may transform from 'information carriers' into 'attack surfaces.' This compels browser vendors to upgrade their security capabilities from 'blocking malicious websites' to 'constraining AI behavior.'

This is why 'having AI in the browser' sounds appealing, but its actual implementation involves numerous engineering details.

One type is the tug-of-war between permissions and privacy. For agents to be useful, they must understand context; to understand context, they inevitably touch user data. Google emphasizes that users can connect or disconnect apps, maintaining control, and plans to introduce more personalized 'Personal intelligence.' This narrative lowers psychological barriers but also means future competition will not just be about model capabilities but about 'who is more trustworthy with authorization.'

Another type is the tug-of-war between explainability and rollback. When traditional apps make mistakes, users know what they clicked; when agents make mistakes, the responsibility chain becomes blurred: was it due to unclear user instructions, model misinterpretation of the page, website structural changes, or inducement by malicious content? If the process cannot be made sufficiently transparent and key nodes sufficiently controllable, users will quickly shift from 'liberating their hands' to 'keeping this thing from acting randomly.'

Thus, 'executing processes in the foreground' is not only a trust-building factor but also compels products to incorporate more complex visualization and auditing: where it clicked, what it filled out, why it did so, and what it plans to do next. By fixing Gemini in the sidebar rather than using pop-up dialog boxes, Google is essentially making way for 'process visibility.'

Looking at competitors, Comet and Atlas are repeatedly mentioned because they have pioneered the narrative of 'AI-native browsers': browsers are not just gateways but operating systems with assistants permanently present. Comet is based on Chromium, and Atlas follows the same Chromium route, essentially indicating one thing: the technological foundation of the browser battlefield is converging, with differences concentrating on three points—account ecosystems, distribution scale, and governance capabilities over 'accident rates.'

Google's strength lies in scale: Chrome's user base allows it to push new interaction paradigms directly to a vast audience rather than slowly educating the market.

OpenAI's strength lies in product mindset: Atlas centers ChatGPT in the browser, unifying the 'conversation as operation' experience and making it easier to form brand associations.

Perplexity's strength lies in the search chain: Comet transforms the 'answer engine' into an 'operation gateway,' emphasizing 'from search to execution' integration more than traditional browsers.

However, whether these strengths can be realized ultimately depends on the same practical issue: when agents begin to 'work' on behalf of users online, they must act like qualified employees—stable, predictable, transferable, and accountable. Otherwise, they will remain confined to demos and lightweight scenarios, becoming 'occasionally used features' rather than 'indispensable daily workstyles.'

This is why discussing browser agents cannot merely focus on model parameters and feature lists; we must also watch for when they can consistently complete tasks without 'dropping the chain' for two consecutive hours.

Conclusion

The integration of Chrome and Gemini 3 may initially appear as a functional update on the surface, but beneath it lies a 'gateway transition': from 'people clicking on web pages' to 'people giving instructions and agents running processes.' For users, this saves time; for the industry, it changes the distribution structure—utility apps will be squeezed, platform traffic will be recalculated, and services that can be smoothly executed by agents will become more valuable.

However, this path will not naturally succeed by merely being 'smarter.' Once browser agents enter real tasks, they will be forced to confront the complexities of the real world: web page structures change constantly, permission boundaries must be clear, malicious inducement is ubiquitous, and the cost of errors is real.

Google, OpenAI, and Perplexity are pulling each other in the same arena; ultimately, the winner may not be the one who can create the most stunning demos but the one who can reduce accident rates to a sufficiently low level, enhance controllability to a sufficiently strong degree, and turn 'doing things on behalf of users' into a default way that people can trustingly entrust.