Advertising is about to get a new gatekeeper

Advertising has always followed buyer behaviour, not the other way around. Search advertising scaled because people searched. Social advertising adapted because attention moved into feeds. Marketplaces monetised because they became the place where decisions were validated.

‍Large language models (LLMs) are now moving into that same position.

LLMs are no longer fringe tools or productivity experiments. They are increasingly where buyers go to understand unfamiliar markets, sense-check assumptions, compare approaches and align internal stakeholders before a single vendor conversation takes place. As that behaviour scales, monetisation is not a hypothetical question. It is an inevitability.

What matters now is not whether advertising will exist inside LLMs, but what kind of advertising it will be, how trust will be protected, and how marketing and sales teams adapt when influence is mediated by a new gatekeeper.

This paper explores how LLMs are evolving into a monetised marketing platform, what early signals tell us about how advertising inside AI will work, and why this shift changes demand creation, attribution and commercial strategy far more than another channel launch ever could.

‍Discovery has moved into the answer layer

Advertising has always followed discovery, and LLMs represent a new consolidation point for discovery.

Rather than searching, clicking and comparing across multiple sources, buyers increasingly ask AI to produce
an answer that already reflects synthesis and judgement. They use LLMs to define categories, identify trade-offs, surface risks and narrow options. This is especially true in complex B2B journeys, where early understanding shapes everything that follows.

This shift is already visible in the data.

Bain & Company found that 80 percent of consumers now rely on AI-generated results for at least 40 percent of their searches, and that this behaviour is already reducing organic web traffic by between 15 and 25 percent. Bain also reports that around 60 percent of searches now end without the user clicking through to another website.

‍^{‍Source: Bain & Company, Goodbye Clicks, Hello AI: Zero-Click Search Redefines Marketing}

Similarweb’s analysis reinforces the same pattern. As AI-driven search experiences roll out, the proportion of searches ending with no downstream website visit has increased sharply, reaching close to 70 percent in some markets.^‍

^{‍Source: Similarweb, The Impact of Generative AI: Publishers}

What this tells us is not that interest is disappearing, but that it is being resolved earlier. More of the buying journey is happening upstream, faster, and in fewer places.

For marketing teams, this creates a familiar tension. Website traffic can fall while category interest remains strong. Search visibility can hold while pipeline becomes harder to predict. Attribution weakens not because performance collapses, but because influence has moved into environments most teams do not yet measure.

The answer layer is where that influence is consolidating.

LLMs are becoming the new gatekeeper

Every advertising platform becomes powerful when it controls the moment where decisions begin to form. Search engines control access to information. Social platforms control access to attention.

LLMs control something slightly different. They control interpretation.

They do not simply retrieve content. They summarise it, frame it, compare it and present it as a coherent narrative. In doing so, they shape what buyers believe matters, what risks they prioritise and which options feel credible.

That matters because the earliest stage of the buying journey has always been the most influential. It is where evaluation criteria are set and assumptions harden. Once those foundations are in place, everything downstream becomes an exercise in confirmation rather than exploration.

That is what makes LLMs a gatekeeper rather than simply another interface. It will be used throughout the buyer journey influencing decisions, and influencing the impact of other marketing efforts.

And when a platform controls enough value, monetisation follows.

‍Monetisation is not speculative, it is already starting

LLMs are expensive to run and increasingly central to how people work, research and decide. No platform in that position remains unmonetised for long.

In 2024, OpenAI confirmed that it would begin testing advertising inside ChatGPT, initially for logged-in users on free and Go plans. The company has stated that ads will be clearly labelled and shown separately from organic answers in early iterations.^‍

^{‍Source: AP News, OpenAI to test advertising in ChatGPT}

Regulators are already paying attention. US lawmakers have publicly raised concerns about how advertising inside AI chatbots could influence users without sufficient transparency, signalling that trust and disclosure will be central constraints on how this market develops.^‍

^{‍Source: The Verge, Senator Ed Markey raises concerns about AI chatbot advertising}

Financial analysts are also beginning to quantify the opportunity. Evercore ISI has estimated that OpenAI could generate up to $25 billion in annual advertising revenue by 2030 if monetisation scales alongside usage.^‍

^{‍Source: OpenAI could generate $25 billion in annual ad revenue by 2030, Windows Central}

This is not because AI companies want to become ad platforms, but because the economics demand it. The more LLMs become the place where discovery and decision-making happen, the more commercial gravity they attract.

What advertising inside LLMs is likely to look like

It is tempting to imagine LLM advertising as simply search ads transplanted into a chat interface. Most credible predictions suggest something far more integrated.

OpenAI has stated they will start by testing ads at the bottom of ChatGPT responses where there is a relevant service to the conversations. Industry commentary and early experimentation point to future advertising that is native to the answer environment, rather than bolted on around it.

Several agency and media analyses suggest likely formats will include:

Contextual sponsored recommendations embedded within relevant answers^‍

^{‍Source: Adweek, What ads in LLMs could look like by 2027}

‍Paid follow-up prompts that guide users toward specific actions or solutions^‍

^{‍Source: WeAreBrain, LLM advertising predictions}

‍Affiliate or referral links surfaced naturally within explanatory responses^‍

^{‍Source: ContentGrip, OpenAI ChatGPT ads monetization strategy (2025)}

Academic research supports this view. Recent papers on LLM-native advertising suggest future systems will need to balance answer quality, user experience and advertiser value simultaneously, rather than relying on simple keyword auctions.^‍

^{‍Source: arXiv, 2512.10551: LLM-native advertising research}

In practice, this means advertising inside LLMs is likely to feel less like paid search and more like paid influence over framing, inclusion and recommendation.

This is important, as it means we cannot use LLM advertising as a replacement for Paid Search or conversion orientated channels, but as an additional opportunity to build awareness and influence the consideration stage.

Can AI still be trusted if advertising is involved?

This is the central tension in LLM monetisation.

Research into user responses to AI-embedded advertising shows that trust collapses quickly when commercial influence is unclear or covert. Users are significantly more resistant to AI recommendations when they suspect manipulation.

‍^{Source: arXiv, 2409.15436: Research on user responses to AI-embedded advertising}

This is why LLM providers are signalling limits. OpenAI has publicly stated that ads will be labelled and separated from answers, at least in early phases.^‍

^{‍Source: AP News, OpenAI to test advertising in ChatGPT}

What most credible commentators predict is not a future where the highest bidder simply buys the answer, but a hybrid model, where:

• Paid placements coexist with organic answers

• Credibility and third-party validation influence whether paid visibility is effective

• Trust, transparency and UX constraints limit how far commercial influence can go

^{Sources:
Keyrus, The AI search revolution: how the shift from Google to LLMs is reshaping (2025)
Forbes, Why LLM advertising could change the search industry (2025)}

In other words, payment may buy access, but it will not replace authority. Brands that lack credibility will struggle to benefit from paid visibility in environments where trust is the core product.

Why marketing and sales teams will feel the impact first

This shift compounds trends that were already under pressure.

6sense research shows that B2B buying decisions typically involve large buying groups, often ten or more people, with the majority of research happening anonymously. Average form-fill rates sit below 4 percent, meaning most intent is invisible even in traditional digital journeys.

‍^{Source: 6sense, The Science of B2B: Buyer Identification Benchmark}

LLMs make it even easier for buying groups to progress without revealing themselves. They can research, align internally, build a shortlist and validate risk without triggering the signals marketing automation systems are built to capture.

This creates a familiar disconnect. Marketing teams see activity without pipeline confidence. Sales teams meet buyers who are informed, opinionated and late-stage. Leadership sees longer cycles and weaker attribution.

The issue is not execution. It is that the point of leverage has moved.

From capturing demand to shaping it

In an LLM-mediated journey, the most valuable outcome is not a click. It is being included, accurately and credibly, when the buying group defines the problem and the shortlist.

That requires a shift in mindset. Visibility alone is not enough. Positioning, proof and consistency become performance levers. Brand stops being a soft asset and starts functioning as infrastructure.

And this is not about creating more content.  As paid placements emerge inside LLMs, the brands that win will be those with already coherent narratives that can create trusted answers.

What marketers should do now

The response is not to chase early ad formats. It is to prepare for a world where discovery, advertising and sales intelligence converge inside AI platforms.

Three priorities matter most:

First, build visibility around real intent, not branded discovery. Buyers start with problems, not vendor names. If you only appear when someone searches for you directly, you are already late.

Second, strengthen trust signals so you are recommended, not just mentioned. Third-party validation, consistent positioning and credible proof will determine whether paid visibility actually converts.

Third, connect AI-led discovery to experiences that create confidence. Your website, content and sales experience must continue the same narrative with clarity and momentum.

The next era of advertising is a gatekeeper problem

Advertising inside LLMs should not be treated as another channel to test. It is a structural shift where influence is won and lost.

The platforms that control the answer layer are becoming the next gatekeepers of demand, and they will be constrained by trust in ways previous
ad platforms were not.

The teams that win will not be those that wait for the rules to be created. They will be the ones that understand how influence is forming now, and prepare to earn and eventually buy visibility in environments where decisions begin.

In the age of LLM-led discovery, the most powerful advertising strategy is not simply visibility. It is becoming credible enough to be trusted by both buyers and the systems that increasingly guide them.