The browser — long the stoic conduit between users and the web — has been remade as an assistant-first platform in 2025, with OpenAI, Microsoft, Perplexity, The Browser Company, Opera and Brave all racing to ship browsers or browser modes that embed large language models and agentic assistants at the UI layer: persistent sidebars, multi‑tab context, cursor chat, and agentic “do this for me” features that can click, fill, and transact on users’ behalf. These changes promise major productivity gains while simultaneously creating new privacy, security and economic trade-offs that could fundamentally reshape how advertising, publisher referral traffic and search monetization work.
AI‑first browsers converge on two core technical ideas: (1) a persistent assistant that has access to page context, open tabs and (optionally) memory; and (2) agentic capabilities — automated, multi‑step flows that act on the web like a human would. Those choices create a single, conversational surface for discovery, synthesis and commerce but also change the browser’s trust model and the web’s economic plumbing. Early reporting and product notes document the same roster of players — OpenAI’s Atlas, Edge’s Copilot Mode, Perplexity’s Comet, The Browser Company’s Dia, Opera’s Aria/Neon experiments, and Brave’s Leo — and repeatedly raise the same central tensions: attention capture versus referral flows, and convenience versus attack surface.
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For end users and IT teams, the sensible posture is pragmatic preparedness: pilot with strict controls, demand provenance and auditable logs for assistant outputs, and prioritize human oversight where accuracy or security matters. Done well, AI browsers will become trusted copilots; done poorly, they will create new systemic risks for privacy, security and the business model of the open web.
(Analysis in this article cross‑checked official product pages and release notes, independent reporting and multiple security advisories to verify platform availability, agentic feature descriptions, pricing signals and documented vulnerabilities.)
Source: Storyboard18 The new face of the browser: Who’s building AI-first browsers, what they do and how they could upend advertising
Background / Overview
AI‑first browsers converge on two core technical ideas: (1) a persistent assistant that has access to page context, open tabs and (optionally) memory; and (2) agentic capabilities — automated, multi‑step flows that act on the web like a human would. Those choices create a single, conversational surface for discovery, synthesis and commerce but also change the browser’s trust model and the web’s economic plumbing. Early reporting and product notes document the same roster of players — OpenAI’s Atlas, Edge’s Copilot Mode, Perplexity’s Comet, The Browser Company’s Dia, Opera’s Aria/Neon experiments, and Brave’s Leo — and repeatedly raise the same central tensions: attention capture versus referral flows, and convenience versus attack surface. What each product is and who owns it
OpenAI — ChatGPT Atlas
OpenAI’s ChatGPT Atlas is a full browser that embeds ChatGPT at its core, shipping initially for macOS with Windows, iOS and Android promised in follow‑on releases. Atlas pairs a persistent ChatGPT sidebar with “cursor chat” for inline editing and a previewed Agent Mode that can perform multi‑step tasks on the web (research, booking, cart filling) for Plus, Pro and Business users. OpenAI describes safeguards (limits on filesystem/app access, pausing on sensitive sites, user approval flows), but also warns agents are not immune to novel attacks.Strengths
- Tight ChatGPT integration and continuity with ChatGPT memory and tools.
- Agentic productivity: agents designed to automate end‑to‑end web workflows.
- Familiar Chromium base preserves extension ecosystem compatibility.
- Privacy and data concentration: embedding ChatGPT, memory and browsing history in one vendor creates concentrated telemetry and regulatory scrutiny. OpenAI provides toggles and incognito modes but defaults and retention policies will determine risk in practice.
- Agentic attack surface: agents that click and fill forms expand prompt‑injection and spoofing attack vectors; OpenAI itself notes the limitations of safeguards.
- Atlas is positioned to serve synthesized answers and complete tasks without a page‑by‑page click-through, a structural shift that could reduce referrals and search ad clicks if users accept synthesized outputs instead of visiting publisher pages. That threatens search‑centric ad revenue models and gives OpenAI leverage over commerce flows.
Microsoft — Edge with Copilot Mode
Microsoft’s play is integration at scale: rather than a separate browser, Edge now ships an opt‑in Copilot Mode that surfaces Copilot as a prominent assistant capable of reading tabs, summarizing content and — with permission — executing actions on pages. Microsoft positions Copilot Mode as enterprise‑friendly (admin control, policies) and experimental/opt‑in on consumer machines. The company documents specific safety measures (visual cues when Copilot is active; blocklists; restricted access to autofill/passwords), and it warns administrators and users about prompt‑injection and other risks.Strengths
- Distribution and integration: Edge is preinstalled on Windows and tied into Microsoft 365 and enterprise management, giving Copilot Mode an instant reach advantage.
- Enterprise controls: group policies and admin governance are already built into Edge’s management model.
- Permission gating and UX friction: many Copilot features are opt‑in, time‑limited, or experimental; the retrofit approach must balance legacy workflows with new assistant behaviors.
- Partial substitution risk: even if Copilot “visits” pages on behalf of the user, how it interacts with publishers (does it fire ad impressions, preserve affiliate tracking, or bypass ad frames?) remains implementation‑specific and materially important for publisher economics.
- Microsoft can redirect value toward its own services (Bing, Microsoft Ads) and subscriptions (Microsoft 365/Copilot tiers). If Copilot replaces SERPs with direct answers, search ad clicks could decline; conversely, Microsoft’s stated emphasis on visiting sites may mitigate referral loss if implemented transparently and with publisher revenue in mind.
Perplexity — Comet
Perplexity’s Comet is a Chromium‑based, AI‑first browser that makes the Perplexity assistant the default experience. Comet emphasizes citation‑first answers and agentic automations; the company initially gated Comet behind high‑tier subscriptions, then broadened distribution by offering a free core with paid premium features. Comet’s central proposition is fast, grounded answers plus multi‑step assistant automation.Strengths
- Citation and grounding focus: Perplexity stresses provenance and visible citations to reduce hallucination risk.
- Agentic automation for power users and enterprises.
- Security vulnerabilities: independent audits and security researchers have exposed prompt‑injection and other risks in Comet’s handling of page content and screenshots; these reports argue that agentic features can be manipulated to exfiltrate data or execute fraudulent flows if not rigorously sandboxed. Perplexity has patched issues but the incidents illustrate a systemic risk in agentic browsing.
- Legal and economic exposure: summarization and extraction raise complex publisher rights questions, encouraging Perplexity to negotiate licensing or subscription approaches.
- Comet’s assistant‑centric answers can short‑circuit click behavior; Perplexity’s business model therefore mixes subscriptions, publisher deals and possible commerce take‑rates, rather than relying on ad impressions alone. The vendor’s layered pricing is an explicit alternate route to monetize attention.
The Browser Company — Dia
The Browser Company shipped Dia as an AI‑native successor to Arc; Dia foregrounds conversational workflows that let you “chat with your tabs,” create Skills and run contextual automations. The product emphasizes design and workflow integration; the company introduced a paid Dia Pro tier (roughly $20/month) to unlock unlimited or heavier AI use. Atlassian’s acquisition of The Browser Company in 2025 (reported publicly) signals enterprise interest and a likely route to broader distribution.Strengths
- UX innovation: Dia’s “chat with tabs” metaphor reduces cognitive load for long research sessions and feels novel in real workflows.
- Design and workflow focus: Dia targets researchers, writers and professionals who benefit from deep synthesis.
- Scale and monetization: as a smaller vendor, Dia must prove subscription conversion and enterprise adoption; product gating (caps on free usage) has frustrated some users, highlighting a common startup tension between growth and unit economics.
- Security surface: agentic features interacting with arbitrary pages require the same sandboxing and permission design necessary across the market.
- Dia’s assistant approach is likely to reduce trivial page visits but could create direct revenue paths (embedded commerce, subscription access to premium content, or enterprise bundles via Atlassian). The product implicitly encourages publisher negotiation — either licensing content or partnering on paid access — instead of relying on incidental ad impressions.
Opera — Aria / Neon
Opera continues to iterate on its in‑browser assistant Aria across Opera desktop, Opera GX and Opera Mini, and in 2025 launched Neon, an AI‑centric browser with agentic automations and a freemium/subscription stance (early access priced at approximately $19.90/month). Opera’s long history with bundled features (VPNs, messaging, gaming tools) makes it well‑placed to experiment with hybrid monetization.Strengths
- Distribution in niche markets: Opera retains pockets of strong adoption and can reuse existing product hooks.
- Hybrid monetization options: free assistant access + paid automations or premium Neon features.
- Model and feature parity: Opera must show that Aria/Neon can match the model quality and extensibility of larger AI infrastructure providers to attract heavy users.
- Opera is likely to continue experimenting with bundled services and subscription revenue, using Neon to sell productivity or power‑user features rather than depending on surveillance advertising. That makes Opera a natural testbed for subscription‑first browser economics.
Brave — Leo / Ask Brave
Brave’s Leo assistant and “Ask Brave” combine Brave Search with privacy‑first answers. Brave’s technical architecture emphasizes anonymized proxying, non‑persistence of conversations for free users, and unlinkable subscription tokens for paid tiers; subscriptions for Leo Premium have been publicly priced (around $14.99/month). Brave’s posture — privacy first, non‑tracking — limits the reach of traditional targeted ads and instead nudges the company (and publishers who partner with it) toward contextual ads, subscriptions or referral‑share deals.Strengths
- Privacy architecture: reverse proxying, non‑retention and unlinkable payment tokens reduce surveillance risk.
- Independence from major cloud providers: Brave can host models or route requests in privacy‑preserving ways that appeal to privacy‑sensitive audiences.
- Smaller reach and narrower monetization: privacy limits precision ad targeting, reducing CPMs relative to surveillance ad models; Brave must rely on subscriptions or contextual ads to sustain heavy AI costs.
- Brave accelerates alternatives to cross‑site tracking: contextual advertising, subscriptions, and paid access to search or assistant capabilities. If assistants reduce click volumes, Brave’s privacy posture forces a marketplace experiment: can publishers be paid without identity‑based targeting?
Common technical and business trade‑offs
1) Attention capture vs. referral economics
All players create the same core risk: assistant answers and agentic automations can short‑circuit the click flows that drive publisher impressions and search ad clicks. That converts previously measurable, monetizable user journeys into internal assistant interactions that the vendor controls. The consequence is a bifurcated revenue set of options for vendors: preserve clicks, pay publishers for summaries, insert assistant‑native placements, or move to subscriptions and commerce take‑rates. Publishers that negotiate early with assistant vendors — or adopt machine‑readable provenance and licensing — will be best positioned to capture value.2) Security and sandboxing are central
Granting assistants the ability to click, fill and transact drastically expands attack surfaces. Reported security incidents with Perplexity’s Comet (prompt injection, screenshot‑based exploits) and repeated vendor advisories on prompt injection illustrate how quickly these risks can become practical exploits. Vendors must adopt permission gating, strict allow/block lists, interaction visibility, and novel defense patterns for agentic browsing (e.g., inference‑time provenance checks and input sanitization). Independent audits should be mandatory before broad enterprise deployment.3) Privacy choices will define monetization
Browsers that center privacy (Brave, certain Opera choices) are more likely to pursue subscriptions, contextual ads or publisher partnerships than identity‑based ad models. Conversely, vendors that control assistant layers and have scale (OpenAI, Microsoft, Google) possess stronger levers to monetize via subscriptions, commerce integrators and internal ad formats — at the cost of regulatory and publisher pushback. That split will shape the ad ecosystem: a privacy‑first lane with lower CPMs and subscription support, and an assistant‑centric lane where centralized answers capture commerce take‑rates and displace referral ad dollars.What publishers and advertisers should do now
- Treat assistants as distribution partners, not invisible extractors: negotiate licensing or API access so summaries and extracts of your content pay for themselves.
- Publish provenance metadata (structured summaries, canonical excerpts, paywall hooks) that makes it easy for assistants to cite and compensate creators.
- Monitor assistant traffic patterns and instrument bot‑like interactions at the same fidelity used for programmatic partners.
- Experiment with direct audience revenue (memberships, email, subscriptions) that are robust to referral decline.
- Push for industry standards on provenance, opt‑in data sharing, and auditable assistant behavior to preserve transparency around how content is summarized and monetized.
Regulatory and enterprise angles
Regulators will scrutinize how AI browsers collect and reuse browsing data, whether assistants train on aggregated user activity, and whether vertical integration concentrates advertising power. Enterprises must treat agentic features as high‑risk productivity tools: enforce admin policies, restrict agentic actions for sensitive accounts, and require auditable logs and provenance metadata before integrating assistants into workflows. Microsoft’s admin controls in Edge and OpenAI’s business beta gating are early examples of vendor responses; enterprises should insist on explicit DLP, attestation and rollback semantics before granting automated agent privileges.Strengths to celebrate — and real dangers to manage
The strength of AI browsers is their potential to collapse repetitive, error‑prone web work into reliable, time‑saving automations: multi‑tab research synthesis, inline content editing, and accessible conversational affordances for users with disabilities. These are genuine productivity gains that will accelerate adoption in both consumer and enterprise settings. At the same time, the risks are not hypothetical: we’re already seeing exploited prompt‑injection vectors, confusing privacy defaults, and business models that could hollow out ad revenues overnight if unaddressed. The technical maturity of models, the clarity of consent design, and the robustness of sandboxing will determine whether the technology is a trusted assistant — or a mechanism for new classes of fraud and surveillance.Short checklist for IT and privacy teams (practical, immediate steps)
- Audit any pilot: require a documented threat model for agentic features and run independent security tests before enterprise rollout.
- Set policy defaults to strict: require explicit per‑site permission for agent actions and disallow agent use on financial, healthcare or identity systems.
- Insist on reversible automation and human‑in‑the‑loop controls for purchases, credential entry and privileged actions.
- Demand clear retention rules for any assistant memory and the option to opt out of training usage.
- For publishers, offer machine‑readable content licenses and tested paywall APIs that assistants can honor.
The bottom line
AI‑first browsers are here, and they change more than the UI; they alter the web’s incentive structure. Vendors are experimenting with several monetization paths — subscriptions, enterprise bundles, assistant‑native commerce and contextual ads — but the underlying economic tension is simple: assistants that answer and act for users can reduce the clickstreams that sustain the ad ecosystem. The winners will be firms that balance convenience with transparent privacy controls, robust sandboxing and commercially fair arrangements for publishers.For end users and IT teams, the sensible posture is pragmatic preparedness: pilot with strict controls, demand provenance and auditable logs for assistant outputs, and prioritize human oversight where accuracy or security matters. Done well, AI browsers will become trusted copilots; done poorly, they will create new systemic risks for privacy, security and the business model of the open web.
(Analysis in this article cross‑checked official product pages and release notes, independent reporting and multiple security advisories to verify platform availability, agentic feature descriptions, pricing signals and documented vulnerabilities.)
Source: Storyboard18 The new face of the browser: Who’s building AI-first browsers, what they do and how they could upend advertising
