OpenAI’s ChatGPT Atlas, Microsoft’s Copilot Mode in Edge, Perplexity’s Comet, The Browser Company’s Dia, Opera’s Aria/Neon and Brave’s Leo together mark a decisive shift: the browser is no longer just an HTML renderer but increasingly a persistent, agentic layer that reads, synthesizes and—when permitted—acts on the web on users’ behalf. These new AI-first browsers and modes promise real productivity gains and new user experiences, but they also introduce fundamental trade-offs for privacy, security, publisher economics and the advertising ecosystem. The next wave of browser innovation will be measured less by rendering speed and extension compatibility and more by how vendors manage data, permissions, sandboxing, and the business model for a web that has historically depended on clicks and referrals.
The browser has been the primary portal to the web for decades, and in 2025 that portal is being remade. Instead of presenting ranked lists of links and leaving users to click through, a growing set of products now places large language models and agentic assistants at the center of the browsing experience. The motivations are straightforward: reduce repetitive work, accelerate research, and provide a single conversational surface that understands the context across tabs, history and user accounts. But the architectural implications are profound: agents that can read pages, interact with forms, and complete multi-step transactions change the browser’s trust model and the economic plumbing of the open web.
This article examines the major AI-first browsers and AI modes that emerged in 2025, explains what they do well, flags major security and privacy concerns, and analyzes how the shift could upend advertising, publisher revenue and enterprise governance.
Source: Storyboard18 The new face of the browser: Who’s building AI-first browsers, what they do and how they could upend advertising
Background
The browser has been the primary portal to the web for decades, and in 2025 that portal is being remade. Instead of presenting ranked lists of links and leaving users to click through, a growing set of products now places large language models and agentic assistants at the center of the browsing experience. The motivations are straightforward: reduce repetitive work, accelerate research, and provide a single conversational surface that understands the context across tabs, history and user accounts. But the architectural implications are profound: agents that can read pages, interact with forms, and complete multi-step transactions change the browser’s trust model and the economic plumbing of the open web.This article examines the major AI-first browsers and AI modes that emerged in 2025, explains what they do well, flags major security and privacy concerns, and analyzes how the shift could upend advertising, publisher revenue and enterprise governance.
Overview of the AI browser landscape
- OpenAI — ChatGPT Atlas: an AI-native browser with a persistent ChatGPT sidecar and an “Agent Mode” that can perform multi-step tasks for users. Initially released on macOS with Windows, iOS and Android planned.
- Microsoft — Edge (Copilot Mode): an opt-in AI mode inside Microsoft Edge that integrates Copilot, accesses tab content with permission, and is tightly integrated with Microsoft 365 and Windows.
- Perplexity — Comet: a Chromium-based AI-first browser with an integrated Perplexity assistant focused on grounded answers, citations and agentic automations; launched from invite-only to wider availability with layered subscription tiers. fileciteturn0file2turn0file11
- The Browser Company — Dia: a design-forward, assistant-first browser that places chat and tab-aware skills at the center of the UX; uses a subscription model for unlimited or heavy AI usage.
- Opera — Aria / Neon: Opera’s Aria assistant across products and Neon as a premium, agentic browser offering automations and power-user workflows. Opera combines freemium distribution with subscription experiments. fileciteturn0file6turn0file19
- Brave — Leo / Ask Brave: a privacy-focused assistant built on Brave Search and designed to provide answers without heavy cross-site tracking, exploring contextual ads, subscriptions and alternative monetization.
OpenAI — ChatGPT Atlas
What it is and why it matters
Atlas embeds ChatGPT deeply into the browsing surface: a persistent ChatGPT sidebar, cursor chat for inline editing, a memory system and an Agent Mode that can automate multi-step workflows (booking, form completion, cross-site research). OpenAI positions Atlas as a “super-assistant” that unifies search, tools and user context inside one window, and it built Atlas on Chromium to retain web compatibility and extension support. Atlas launched on macOS and is rolling toward other platforms. fileciteturn0file0turn0file14Strengths
- Seamless ChatGPT integration — the same conversational model and memory features users already know from ChatGPT are available in the browser context, enhancing continuity across devices and sessions.
- Agentic productivity — Agent Mode enables complex, multi-step tasks that can significantly reduce manual web work for planning, bookings and document editing.
- Rapid iteration and UX focus — a split-pane default that shows both webpage and live assistant transcript reduces context switching and can speed comprehension.
Weaknesses and risks
- Privacy and trust questions — consolidating browsing data, memory and model interactions in a single vendor ecosystem concentrates sensitive telemetry and raises regulatory scrutiny. OpenAI has controls (memory toggles, incognito) but the default behaviors and retention policies are questions users and regulators will watch.
- Agentic security surface — giving agents the ability to click, fill forms and transact increases the attack surface for prompt-injection, spoofing or malicious sites that try to manipulate agents into undesirable actions. UI affordances like “take control” and “stop” help, but robust sandboxing and permissioning are essential. fileciteturn0file0turn0file7
- Strategic challenge — displacing Google’s dominant search and Chrome ecosystem is difficult; Atlas’s success depends on user adoption, trust and whether it meaningfully diverts search/referral flows. Short-term market reactions to Atlas’s announcement reflected investor sensitivity to search-market disruption.
Advertising implications
Atlas can centralize queries and task flows through OpenAI’s assistant layer, reducing clicks to publisher sites and taking the “referral” out of many information-seeking journeys. That is a structural threat to search-driven advertising: if users receive synthesized answers and agent-executed outcomes, traditional search ad impressions and publisher pageviews decline. OpenAI could monetize with subscriptions and direct commerce integrations, creating a parallel revenue model that sidesteps classic ad networks. fileciteturn0file0turn0file7Microsoft — Edge with Copilot Mode
What it is
Rather than building a separate AI browser, Microsoft has retrofitted Edge with Copilot Mode—an opt-in experience that places Copilot at the core of new tabs and can access open tabs and user context when the user consents. The feature ties into Microsoft 365, Teams and Windows, and Microsoft emphasizes visibility (showing actions live), enterprise controls and gradual rollout. fileciteturn0file13turn0file3Strengths
- Ecosystem integration — Copilot benefits from Microsoft’s enterprise reach, Office ecosystem and Windows distribution, making it a natural productivity layer for business users.
- Enterprise controls & policies — admins can toggle Copilot capabilities for managed devices and configure policies, which makes Copilot more palatable for organizations than consumer-only offerings.
- Transparency-first UX — showing Copilot’s actions live and making it opt-in are meaningful UX decisions that can improve trust.
Weaknesses and risks
- Feature gating & experimental mode — many capabilities are permissioned, experimental, and sometimes limited to paid tiers or trials, so the user experience is in active iteration and not yet uniform.
- Retrofit limits — converting an incumbent browser into an AI-first experience requires careful design to avoid breaking legacy workflows; some argue an AI-native build can offer cleaner UX.
- Publisher economics ambiguity — Microsoft claims Copilot can preserve publisher traffic by actually visiting pages, but how that translates into ad impressions, affiliate clicks or measurable revenue is uncertain and depends on detailed interaction policies.
Advertising implications
Copilot’s integration with Microsoft services creates opportunities for alternative monetization: subscription bundles (Microsoft 365 Premium), enterprise licensing, and assistant-native placements or commerce links. If Copilot truly routes traffic to publishers, ad revenue may be preserved; if it substitutes synthesized answers for original pages, search ad clicks and publisher impressions may still decline. The product decisions here will materially affect publishers’ economics.Perplexity — Comet
What Comet does
Comet is a Chromium-based AI-first browser that integrates Perplexity’s citation-focused assistant as the default search and assistant surface. It emphasizes grounded answers with visible citations and agentic automations that can summarize pages, synthesize across tabs and—behind paid tiers—execute multi-step workflows. Perplexity initially launched Comet behind a high-priced tier, then shifted to a free core browser with paid premium features to accelerate distribution. fileciteturn0file2turn0file11Strengths
- Citation-first grounding — Perplexity’s emphasis on source citations aims to reduce hallucinations and provide provenance that users and publishers can inspect.
- Agentic automations for power users — advanced features (background assistants, multi-step automations) are gated behind paid tiers for monetization while the core product is broadly available.
- Rapid adoption strategy — moving the core browser to free lowered the barrier to growth and increases telemetry and negotiating power with publishers and partners.
Weaknesses and risks
- Security findings and prompt-injection risks — independent audits and security analyses have flagged vulnerabilities in Comet’s handling of web content, screenshots and the agent interface; these highlight the real-world dangers when assistants get deep access to page content. fileciteturn0file2turn0file12
- Legal exposure from content reuse — Comet’s summarization and extraction model raises publisher rights issues; Perplexity’s publisher revenue programs attempt to mitigate that but are not legal shields. filecite
- Compute & sustainability — a free AI browser that provides heavy assistant usage is expensive to operate; Perplexity’s move toward layered subscriptions is a pragmatic response, but financial viability depends on conversion rates.
Advertising implications
Comet can reduce referral traffic by synthesizing and displaying content directly in the assistant sidecar. Perplexity’s layered monetization—free core plus paid Pro/Max tiers and publisher-sharing experiments—illustrates how startups may seek to replace ad-driven revenue with subscriptions and direct deals. The central risk for ad ecosystems is the steady erosion of click-throughs that historically routed user attention (and ad impressions) to publishers. fileciteturn0file11turn0file12The Browser Company — Dia
Product positioning
Dia, the follow-up to Arc, is an assistant-first browser that aims to reduce tab overload by letting users “chat with their tabs.” Its design emphasizes conversational workflows, custom skills, and a subscription tier (Dia Pro) that unlocks heavier AI usage. The product was praised for design and for rethinking browser UX around an assistant rather than around tabs. fileciteturn0file4turn0file6Strengths & limits
- UX innovation — Dia’s conversational focus and “chat with tabs” metaphor can materially speed research and information management for writers, students and researchers.
- Product-market fit challenges — as a boutique product, Dia faces distribution and monetization constraints; subscription pricing (e.g., $20/month Pro) limits its appeal to heavy users.
- Security & integration concerns — as with other AI-first browsers, Dia’s agentic interaction with arbitrary web pages raises security considerations that must be addressed through permissioning and sandboxing.
Advertising implications
Dia’s assistant-first UX can reduce simple click-throughs to ad-funded pages while opening avenues for direct commerce, embedded partnerships and subscription-based access to premium content—models that sidestep the display ad paradigm. Enterprise interest and reported acquisition conversations hint at alternative distribution avenues beyond consumer display ads.Opera — Aria and Neon
Opera has leveraged Aria—the company’s assistant—across multiple products and launched Neon as a premium, agentic browser for power users. Opera’s long history of bundling value-added features (VPN, messaging, gaming tools) positions it to experiment with hybrid monetization: free assistant experiences plus paid premium automations. Opera’s installed base in selected markets gives it a distribution advantage not all startups can match. fileciteturn0file6turn0file19Advertising implications
Opera’s history suggests a readiness to use alternative monetization: bundled services, partnerships, and subscription revenue rather than purely contextual or surveillance-based ads. Neon’s premium pricing and Aria’s free availability illustrate hybrid strategies—replace some ad exposure with subscriptions or direct commerce hooks.Brave — Leo and Ask Brave
Brave emphasizes privacy-first AI assistance: Leo and Ask Brave aim to provide contextual answers while minimizing cross-site tracking and using Brave Search as a backbone. That positioning makes Brave an outlier in the snippet economy: rather than monetizing via personalized tracking, Brave is more likely to lean on contextual ads, subscriptions and privacy-preserving monetization experiments. That approach will appeal to users and publishers uneasy with surveillance advertising but limits the precision of ad targeting and hence ad CPMs.What this means for advertising and publishers
The structural threat: attention capture vs referral flows
AI assistants and agentic features can short-circuit the classic click-through model. When a browser assistant answers a user’s question directly or completes a purchase without navigating to the publisher’s page, the chain of events that produced ad impressions and search ad clicks breaks. This reduces publishers’ ad inventory, weakens referral analytics and threatens affiliate and referral-based models. Vendors can monetize the assistant layer directly—via subscriptions, commerce take-rates or assistant-native sponsored placements—creating a competitive pressure on the ad ecosystem. fileciteturn0file7turn0file11New ad placements and assistant-native monetization
- Assistant-native recommendations and sponsored answers: vendors can create ad-like placements inside the assistant UI.
- Commerce integrations and affiliate models: assistants can generate revenue through transactions, booking fees or direct commerce partnerships.
- Subscription and enterprise revenue: owners of assistants can charge for uninterrupted, high-quality model access and premium automations.
- Contextual, privacy-preserving ads: browsers like Brave may push contextual ads that do not rely on cross-site tracking.
Short-term and medium-term publisher strategies
- Negotiate licensing and API deals with assistant vendors so content used in summaries is compensated.
- Publish machine-readable provenance metadata and paywalls tuned for assistant interactions.
- Experiment with subscription and membership models that reduce dependence on referral ad traffic.
- Monitor assistant behavior and take technical measures (rate limiting, bot-detection signals) where appropriate.
Security and sandboxing: the non-negotiables
Agentic assistants introduce new attack vectors:- Prompt injection: malicious pages can try to steer an agent to reveal secrets or perform harmful actions.
- Automation abuse: agents that fill forms or execute transactions can be manipulated into fraudulent behavior.
- Screenshot/executable content risks: agents that parse or act on images and file uploads can be tricked by crafted inputs.
Privacy: defaults, memory and regulatory scrutiny
The most sensitive design choices are defaults: what data is stored, who has access, and whether assistant interactions are used for model training. Memory features that improve personalization are useful but also concentrate risk. Vendors that default to opt-in memory, provide clear scrubbing and export controls, and publish transparent data-handling policies will win more trust. Regulators are already scrutinizing data use and antitrust implications when a single assistant layer controls search and browsing; vendors should expect inquiries into consent defaults, retention and profile-building. fileciteturn0file7turn0file18Enterprise and IT implications
For IT teams, the right posture is cautious pragmatism:- Pilot agentic browsers in controlled accounts and monitor agent actions against internal apps.
- Require MFA and hardware-backed keys for accounts that agents might access.
- Use policy controls to restrict agent functionality on corporate devices.
- Preserve deterministic and auditable systems for regulated work—use AI assistants as supplements, not authoritative workflows. fileciteturn0file7turn0file16
Strengths and the likely arc
Strengths across the field are palpable: measurable productivity wins, accessibility improvements from conversational interfaces, and faster research workflows. Competition will also accelerate innovation and help define best practices for provenance, permissioning and auditability. The short-to-medium arc looks like this:- Rapid feature rollout and experimentation.
- Iterative hardening (sandboxing, UI affordances, permission models).
- Regulatory attention and publisher negotiations.
- Maturing revenue models: subscriptions, assistant-native commerce, and contextual ads.
- An equilibrium where trusted vendors combine convenience with transparency and robust privacy controls. fileciteturn0file17turn0file6
Cautions and unverifiable claims
A few claims remain uncertain or site-dependent and should be treated cautiously:- Market-share disruption timelines: while headlines show investor concern, the pace at which users switch default browsers and the long-term impact on Google’s search ad revenue remain speculative and contingent on adoption and retention. Short-term stock moves are noisy and not definitive proof of structural change.
- Exact security posture of each product at scale: vendors publish controls, but only extensive third-party audits and real-world deployments will reveal how resilient their sandboxing and permissioning are. Some independent reports flagged vulnerabilities in early builds; these indicate risk but not definitive compromise of long-term product safety. fileciteturn0file2turn0file12
- Publisher compensation outcomes: many assistant vendors are exploring revenue-sharing or publisher programs, but the effectiveness and fairness of those programs are still emerging and will be tested in negotiations and likely litigation.
Practical takeaways for WindowsForum readers
- Treat agentic AI browsers as powerful productivity tools that also increase attack surface and privacy exposure. Test new browsers in sandboxed profiles before making them your daily driver.
- Review privacy defaults aggressively: disable memory or telemetry if you do not want browsing activity to be retained or used for model training.
- For organizations, pilot cautiously and use policy controls to restrict forms of agentic automation that can touch corporate systems. Require explicit confirmation for any transaction-related automation. fileciteturn0file7turn0file16
- Publishers should engage vendors for compensation frameworks, publish clear provenance metadata, and consider diversifying revenue through subscriptions and membership models.
Conclusion
AI-first browsers are more than a set of new features—they redesign the browser’s role from passive renderer to active assistant. The winners will be those who combine compelling productivity gains with ironclad privacy, explicit permissioning, strong sandboxing and transparent monetization models that recognize the needs of publishers and enterprises. The evolving landscape offers genuine opportunity: faster research, better accessibility, and new commerce experiences. But it also poses real risks to security, privacy and the ad-funded economics of the open web. The coming months and years will determine whether these agents become trusted coworkers—or whether their convenience will require a deeper regulatory and contractual restructuring of how content creators are paid and how user data is governed. fileciteturn0file11turn0file17Source: Storyboard18 The new face of the browser: Who’s building AI-first browsers, what they do and how they could upend advertising
