Emerging AI-powered browsers like ChatGPT’s Atlas and Perplexity’s Comet are challenging Google’s long-standing monopoly—transforming how people find, decide, and buy. As search behavior moves from searching and clicking to asking and doing, the implications for B2B discovery, advertising, and visibility are profound.

In this issue:

• The New Search Wars: AI Browsers Challenge Google’s Dominance

• Advertising in the Age of LLMs: What Happens When AI Becomes the Ad Platform

The New Search Wars: AI Browsers Challenge Google’s Dominance

For two decades, "Googling" served as the internet's operating system with a de facto search engine monopoly. But that dominance is now facing its first structural test.

The threat isn't coming from a faster browser; it's coming from a fundamental shift in how users behave. We're not seeing a repeat of the Chrome vs. Firefox wars. Instead, challengers have entered the arena that are competing on user intent instead of browser speed. Search and discovery have flipped on their heads, moving from "searching and clicking" to "asking and doing."

The New Contenders: Agents Over Search Bars

Google faces its challenge from browsers designed to act on information rather than merely index it. In other words, these "agentic" tools change the user experience from information retrieval to task delegation.

• OpenAI’s Atlas: Launched in October 2025, this tool positions itself as a "super assistant" instead of a traditional browser. Its "Agent Mode" goes beyond queries to full workflows: comparing flights, opening pages, and compiling options into a shortlist to avoid the dreaded tab juggling.

• Perplexity’s Comet: Comet is positioning itself to move users "From Answers to Action". It’s built to delegate high-intent tasks—like "buy a high-quality office chair" or "book a meeting based on this email". It already has 15 million monthly active users.

• Arc: While Atlas and Comet fight for the consumer, Arc seems to be focused on the productivity power user. Its AI features focus on synthesis, like summarizing tabs and automating research workflows to eliminate annoying manual tedium.

While these challengers may initially treat Google’s search index as a backend utility, strategic moves—such as OpenAI’s development of an AI search engine, the launch of its own browser, and plans for integrated ads—indicate that these tools are fundamentally competing to become the user's primary destination.

The B2B Cascade is Faster Than You Think

Here’s a critical wake-up call for US marketers: far from a consumer trend waiting to trickle down, this is a B2B-led reality.

Forrester reports that B2B buyers are adopting AI-powered search at three times the rate of consumers. In the US specifically, the acceleration is even more dramatic: 48% of US buyers now say they use GenAI for vendor discovery, compared to just 14% in other regions. Furthermore, 90% of organizations report using generative AI in some aspect of their purchasing process.

Navigating the “Rainy Day” of Search with David Fox

At 6sense Breakthrough, we had one of those rare conversations that stops you in your tracks. In a sea of opinions about AI search, David Fox, Bloomerang’s Search & AI Optimization Manager, stood out immediately. It’s not often we meet someone who can keep pace with how fast this space is moving — and how dramatically it’s reshaping B2B discovery.

His perspective aligned with what we’re seeing across our client base: disruption isn’t something to fear — it’s leverage for teams willing to adapt faster than their competitors.

Fox argues that while this shift may feel destabilizing for incumbents, it creates a once-in-a-decade opportunity for agile brands to outmaneuver category giants.

The “Indirect Relationship” Reality 

Marketers should accept that the direct line to the customer is fading. "For a long time, we had a really great thing going where we got to talk directly to the people that were looking for products and services,” explains Fox, “and we're not going to have that anymore.” This means elements like your website speed matters less than your ability to feed accurate data to the agent representing the buyer.

And accuracy is key. Before optimizing for AI, ensure your product or solution reality matches your competitive claims. As Fox warns, "If the answer is no [we aren't better than our competitors], that's not really an SEO issue. You might have to do some soul searching.”

Our Head of Marketing, Gina Inks, reinforces this pivot away from traditional tactics: “We’re moving out of an era where search rewarded surface-level optimization like keywords, backlinks, and structural signals into an AI-driven era that prioritizes meaning.”

The Rainy Day Opportunity for Underdogs

Fox views the current volatility as a reset button. He uses a racing analogy: "If it's great weather outside in a race... It's going to be really hard to overtake three cars. But if it's raining, you could overtake ten.” For B2B challenger brands, this is the rainy day. "Now is the time to try new things, especially if you're an underdog,” Fox notes. “You can go up against these domains that are massive and you might win".

However, the sheer volume of traditional search still matters. Our Senior Team Director of SEM, Aaron Woolway, provides the necessary context on Google's current relevance: 

"Google Search is still relied on massively, as there are over 5 Trillion+ searches annually.” He adds, “Chat GPT is for people seeking information and practical guidance/writing, but Google is still the source for looking for and discovering products and is present in half of the discovery for new brands, products, and research.”

The Future of Monetization

Where is the ad model going? Woolway thinks, “Early ideas on monetization will likely be ads on unpaid subscriptions, similar to how music apps like Pandora are set up.” Fox’s theory is that companies like OpenAI could monetize the second prompt in a conversation, rather than the first. While the first prompt delivers a "golden goose" answer, the second prompt implies specific intent and carries reliable user data from the first prompt for direction. "You could probably monetize the second prompt,” he offers, “without poisoning the well of why you're valuable to general consumers right now.” 

The New Playbook: Structured, Cited, and Trusted

As recent analysis from Artefact notes, AI agents are programmed to evaluate products based on "logic, rules, and signals" rather than clever copywriting or brand sentiment. A claim on your own website is marketing; a claim cited by a third party is a fact. Inks notes, “This shift should feel both comforting and exciting. When you speak directly to your audience’s needs with expertise and authenticity, AI search systems can actually understand it, and reward it."

We’re helping enterprise teams implement a three-part framework to secure their place in the answer:

1. Be Structured (The Prompt Graph): You need to "model the graph" of user intent. Use structured data (like schema markup) and break content into liftable chunks (tables, clear H2s) that answer specific sub-tasks so AI agents can easily ingest them.

2. Be Cited (Digital PR): Marketing claims on your own site hold less weight. Seed your facts and leverage press releases to get on third-party platforms that the AI treats as sources of truth, such as peer review sites (G2, TrustRadius, Capterra) and community forums like Reddit.

3. Be Trusted (Experience): Google’s own guidance confirms that "structured data" and a "great page experience" are the keys to appearing in AI overviews.

This focus on experience validates what we discussed last month on UX as a differentiator. With AI, a great page experience proves your credibility and usability to the machines that inform buying decisions. UX is where personalization becomes tangible.

The Next Era of Visibility

Solutions like our AI Results Blueprint and ROI·DNA Spark frameworks work emerged from this exact shift.

We focus on answerability—how machines read, interpret, and decide whether your brand deserves to be surfaced. These frameworks help enterprise teams strengthen the signals that matter most in an AI-led discovery landscape.

The search wars have evolved beyond who has the best list of links; the winner will be the one who earns the trust of the agent. The brands that prepare their data for this "asking and doing" reality will own the next era of visibility.

Advertising in the Age of LLMs: What Happens When AI Becomes the Ad Platform

A new phase of digital discovery is accelerating, and it’s happening faster than anyone predicted. What began as scattered experiments in AI-assisted browsing has turned into a structural shift in how people evaluate, decide, and act online. In APAC alone, IDC forecasts that enterprise investment in GenAI will grow faster than any other global region through 2027, signaling where business behavior is already heading. This is no longer about new interfaces; it’s about new decision-making systems.

As AI browsers like ChatGPT’s Atlas, Perplexity’s Comet, and Arc redefine how users engage with information, they’re also setting the stage for the next frontier: AI-native advertising. Not ads that sit beside results, but influence embedded directly within the reasoning layer itself. For marketers, this represents the most significant shift in digital influence since the programmatic wave, one which moves discovery from searching and clicking to asking and doing.

And as this shift accelerates, we believe a new advertising model is forming, one that brands must prepare for long before the monetization layer arrives.

1. When AI Becomes the Interface, What Becomes the Ad?

LLM-powered browsers operate fundamentally differently from traditional search engines. Instead of offering links, they synthesize, evaluate, and contextualize, becoming the first point of interpretation, not just the first point of discovery.

That means the “ad slot” of the future won’t be a blue link or a sidebar banner. It will live inside the conversation.

Below are the most plausible monetization models emerging as AI ecosystems mature:

A. Sponsored Citations

AI answers are built on sources such as documentation, websites, benchmarks, analyst reports, product pages, and more. In the future, these citations could become:

• Sponsored placements

• Priority sources

• Brand-verified content modules

This model mirrors SEM but within an AI explanation.

B. Conversational Recommendations

Agents like Atlas and Comet already surface products and tools contextually. The monetized version might look like:

Think Amazon’s “Sponsored Products”, but embedded within an AI-generated buying journey.

C. Action-Driven Ad Units

This is the most transformational model where ads don’t ask for a click but offer an action:

• “Would you like me to build this report using Vendor X?”

• “Should I generate a comparison with Provider Y?”

• “Want me to schedule a demo with Z?”

Advertising becomes agentic, powering decisions, not just discovery.

D. Personalization via Synthetic Personas

In APAC, where digital identity and behavior differ dramatically across markets, LLM-driven advertising could adapt to cultural nuance, language, and localized buying expectations, a direction early testing in ROI·DNA Spark already hints at.

2. We've Seen Inflection Points Like This Before

To understand the future of AI advertising, it helps to remember its predecessors:

• SEO → SEM: monetization came from prioritizing visibility

• Programmatic: monetization came from automating relevance

• Social algorithms: monetization came from influencing feed curation

LLMs represent the fourth major advertising inflection point.

But for the first time, ads won’t be placed around content.
They’ll be woven into the reasoning layer itself.

This is why the shift is profound. Influence moves from the page to the model, and every brand must understand how that model sees, interprets, and ranks them.

3. The Challenge: Trust, Bias, and the New Measurement Problem

AI advertising faces hurdles far larger than any previous digital shift:

A. Trust

Users won’t tolerate “hidden influence.”
Regulatory bodies across the U.S., EU, Singapore, and Australia have already signaled through AI governance frameworks and transparency requirements that algorithmic explainability will be essential for AI-driven recommendations.

B. Bias

If AI models over-prioritize sponsors, they risk degrading answer quality and adoption.
Expect a balancing act between revenue and credibility.

C. Measurement

How do you measure:

• Influence inside a conversation?

• Brand presence inside an LLM answer?

• The role of AI reasoning in a purchase?

The traditional marketing funnel collapses when the assistant handles awareness → evaluation → action in one prompt.

This is why marketers need to instrument their presence now before monetization rewires the landscape.

4. Preparing for the AI Ad Era: What Marketers Must Do Today

Even without a formal ad layer, the groundwork for AI advertising is already being laid. And the leading indicator of future performance is present-day visibility inside LLMs.

This is where ROI·DNA and Hotwire’s AI Lab ecosystem becomes essential.

A. Understand Your AI Visibility (ROI·DNA Spark)

ROI·DNA Spark, adopted by brands like Pure Storage and Equinix already analyzes:

• How your brand appears across ChatGPT, Gemini, Copilot, and Google AI Overview

• Which sources inform AI answers

• How different personas receive different results

• What structural gaps exist in your content

In other words:
Spark is optimization for the AI era, before the AI ad era begins.

B. Strengthen Your Data & Evidence Layer

AI models reward structure and credibility:

• Clear product documentation

• First-party insights

• Robust metadata

• Publicly verifiable claims

• High-quality content with domain authority

This is tomorrow’s ranking system.

C. Build Intelligence for Precision Targeting (ROI·DNA Ignite)

ROI·DNA Ignite, now in beta with Red Hat and SAP Concur, uses RAG to blend:

• Web data

• Technographic signals

• Wallet share

• Internal account engagement

…into AI-driven account prioritization.

When AI ads arrive, this intelligence will determine which audiences are worth influencing and how.

D. Prepare Creative for a Conversational Environment

Brand voice, proof points, and differentiation must be rethought for:

• Dialogue

• Decision support

• Multi-step reasoning

• Summaries and comparisons

This is messaging designed for agents, not algorithms.

5. The Future of Advertising Is Trust

AI advertising is coming, whether in six months or six years. But the era of “bidding for clicks” is ending.

The next battleground is earning trust inside the conversation.

Brands that:

• understand how AI interprets them,

• optimize their presence today, and

• build credibility through structured, verifiable content

…will dominate the first generation of AI-native advertising.

For everyone else, the gap will widen fast.

Because as the search landscape becomes conversational and contextual, the brands preparing now won’t just stay visible, they’ll define the future of discovery itself.

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