Publishers and search engines have long depended on ad placements and affiliate marketing to make money.
Search engines rely on pay-per-click (PPC) models, while publishers blend display ads, affiliate links, and sponsored content.
But with chat-based AI platforms like ChatGPT, Claude, and Perplexity on the rise, that foundation is starting to crack.
If users get the information they need directly from AI, why would they keep clicking search ads or publisher display links?
And as search engines push further into AI-driven results – including features like Google’s AI Mode – what incentive remains for users to engage with traditional ad units?
If fewer people reach publisher sites at all, the core revenue models that have supported the open web begin to break down.
The real numbers behind AI’s impact
AI’s effect on the open web isn’t hypothetical – it’s already visible in the data.
Google’s advertising revenue continues to grow, reaching $348.15 billion in 2024, but the growth rate is slowing.
Year-over-year gains fell to 13.9% between 2023 and 2024, down from 41.3% during the pandemic.
Broader economic factors played a role, but the trend also reflects fewer clicks and Google’s struggle to monetize AI-powered search features.
Publishers are seeing even sharper declines.
In September 2025, DMG Media reported an 89% drop in click-through rates, pointing directly to AI Overviews as a primary cause.
Zero-click searches now make up nearly 60% of Google’s mobile queries, and AI Overviews appear for roughly 30% of processed searches.
Informational publishers are hit hardest, as their content is often summarized before users have a reason to visit their sites.
The Guardian recently noted that sites previously ranked first can lose up to 79% of traffic when pushed below an AI Overview – a trend some outlets describe as a “traffic apocalypse.”
These numbers highlight a clear shift: users are getting what they need from AI-generated answers, not from publisher pages or traditional SERPs.
With this foundation established, it’s clear why AI is reshaping publisher revenue models – and why search engines are feeling similar pressure.
Dig deeper: The implosion of the blogging-for-dollars revenue model
How AI is reshaping the economics of the open web
Publisher pressures
Publishers have long relied on paywalls, a trend that accelerated when featured snippets – now often replaced by AI Overviews – started answering queries directly.
AI platforms like Google AI Mode, Gemini, Claude, and ChatGPT push this further.
If users get answers without ever reaching a publisher’s site, they never hit the paywall and never become subscribers.
The result is a quieter, more invisible form of loss.
Users don’t realize what content isn’t being used to generate their answers, and publishers that lock down too aggressively risk losing reach, voice, and influence.
Subscription fatigue only adds to the challenge as consumers juggle multiple paid media services and may not see the value in text-based content alone.
Sponsored content faces its own risks.
While it may still influence users, attribution will get harder as AI platforms surface insights without sending traffic back to the source.
Engagement may appear to come from AI providers instead of the publisher, creating another measurement gap in a long line of industry-wide data erosion.
The decline of ad-based models – and how publishers can respond
If users no longer visit publisher sites, they won’t see display ads, click affiliate links, or trigger video streams.
Fewer impressions push CPMs down, affiliate revenue drops as AI responses rarely include those links, and video ad inventory shrinks as fewer people load video-heavy pages.
To stay viable, publishers will have to rethink how they monetize and deliver value in an AI-driven environment.
Subscriptions may still work, but they need to offer more than text – such as exclusive tools, unique data, or bundled services.
With traditional advertising weakening, publishers may need to explore partnerships with AI platforms, invest in first-party data, or shift toward metrics that measure influence and visibility rather than clicks.
Sponsored content and affiliate programs aren’t necessarily doomed, but they will require new approaches. This may include:
Working directly with AI providers to ensure proper attribution.
Integrating products and services more deeply into the publisher’s own ecosystem.
Experimenting with formats that are more challenging for AI to abstract away.
Publishers that diversify revenue, test emerging models, and find ways to stay visible in AI-driven environments will be far better positioned than those who double down on legacy tactics.
Dig deeper: How AI media partnerships influence your brand visibility in genAI: Research
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Search engine pressures
Search engines face a direct threat as AI answers reduce the need for traditional search behavior.
PPC advertising remains their primary revenue source.
This dependency is exactly why companies like Google delayed releasing their AI technologies until competitors forced their hand.
Google has been developing similar capabilities for years, but its business model is tightly tied to clicks across its properties.
AI-generated answers don’t produce those clicks, leaving Google with powerful technology that undermines its own revenue engine.
Microsoft’s Bing faces similar constraints, while smaller players like DuckDuckGo or Brave may be able to adapt more quickly.
Zero-click behavior will also accelerate. Google created much of this dynamic long before the advent of generative AI through the introduction of featured snippets.
Now, AI Overviews and AI chatbots amplify it.
Whether users adopt AI-driven search features like Google’s AI Mode or bypass search engines entirely for standalone AI tools, fewer clicks will be generated across the board – a clear revenue threat for every search provider.
A broader shift in user behavior is also underway.
As AI tools become more capable and trusted, traditional search will lose relevance.
This transition won’t happen overnight, just as the early internet took time to evolve into a mainstream commercial environment.
But the trajectory is clear: over time, more queries will move to AI platforms that give direct answers, not links.
Advertiser confidence may erode as search audiences shrink.
If fewer people rely on search engines, advertisers won’t be able to reach the same volume of users at the same cost.
Search engines will need new monetization paths before this tipping point arrives.
Supporting search verticals like maps, news, and shopping will also feel the impact as AI tools begin producing richer, more connected answers that further reduce traditional search traffic.
The weakening of search ad models – and how engines may adapt
Traditional PPC ads face declining clicks and impressions, which reduces ROI for advertisers and shrinks revenue for engines like Google.
Display advertising suffers for similar reasons.
If publisher sites receive less traffic, partner sites across the Google Display Network generate fewer impressions – a problem for both Google and the publishers themselves.
As AI becomes more integrated into daily online behavior, advertising competition will diversify.
Advertisers will likely use a wider mix of platforms, leading to a web that’s more distributed and less dominated by any single search giant.
That’s healthy for the ecosystem but challenging for companies like Google, whose dominance relies on controlling the paths users take to information.
Search engines will increasingly need to function as AI platform leaders, not just retrieval systems.
While Google, Bing, and others are developing AI tools to keep pace with OpenAI and Anthropic, the challenge goes beyond technology.
Their organizational structures and revenue models must evolve quickly – something large companies often struggle with.
Even if tools like Google AI Mode or Gemini improve, the bigger question is whether these companies can restructure fast enough to stay relevant.
To survive, search engines will need new revenue channels. Traditional PPC and display ads won’t be sufficient.
Engines may explore premium AI subscriptions, paid features, or ads embedded directly into AI responses.
Sponsored AI content and AI-native ad formats could replace click-based models.
Measurement will need to shift as well, with greater emphasis on engagement, brand lift, and conversions rather than impressions or CPC.
Ultimately, flexibility will determine which platforms endure.
Large engines must overcome legacy systems that slow adaptation, while smaller or newer entrants may be able to innovate more aggressively.
Experimentation, careful tracking of user behavior, and deeper integration of AI features will be critical in shaping the next generation of search.
Dig deeper: AI search & the shift towards inauthenticity & commercial interests
Scenario planning: What different levels of AI adoption mean
AI adoption won’t rise evenly across all users or all query types.
Different levels of reliance on AI answers will create very different outcomes for publishers and search engines.
The scenarios below outline how the landscape could shift as adoption accelerates.
Scenario 1: 30% AI query adoption (current)
AI already generates snippets for nearly a third of search queries, primarily for simple informational questions such as “how to do X” or “what are the ingredients for Y.”
Publisher impact
Display ad revenue drops sharply for informational and news sites.
Advertisers running display campaigns also see weaker returns.
Affiliate revenue declines.
Publishers with unique analysis or exclusive data hold onto more traffic and may earn AI citations, but still take a hit.
Newsletters regain importance as publishers focus on direct audience relationships.
Search engine impact
Google keeps its lead, but margins tighten – for Google and for advertisers.
PPC remains resilient for commercial-intent queries.
Most vulnerable
“How to” sites, news aggregators, mainstream news outlets, and basic product review sites.
Scenario 2: 55% AI query adoption (medium term)
AI now satisfies more than half of all queries.
Traditional search becomes secondary for task-focused needs, pushing marketers to find new ways to promote their clients as search loses profitability.
Publisher impact
Ad-dependent publishers lose 40-60% of their search traffic, which for many is their main source of visits.
Subscription models falter because users never hit the paywall – AI pulls useful snippets directly into results.
Brands with strong recognition or exclusive first-party data retain more traffic.
Small and mid-sized publishers begin consolidating or closing because content creation no longer pays.
Search engine impact
Paid search revenue drops significantly.
Display network partners face severe declines.
At this stage, search engines may pursue licensing deals with major publishers, though it’s unclear whether the economics would work for either side.
Most vulnerable
Mid-sized news outlets.
Niche publishers in areas like travel, health, and finance.
Affiliate-heavy sites.
Scenario 3: 85% AI query adoption (long term)
AI becomes the primary interface for finding, retrieving, and consuming information.
AI platforms – search-integrated or standalone – share dominance at the scale Google holds today.
Traditional search remains only for specific use cases, much like information-retrieval methods after SEO emerged.
Publisher impact
Traditional publishing business models largely collapse.
Only premium subscription publishers with deeply loyal audiences survive in familiar form.
Content creation shifts toward licensing deals as publishers act more like data suppliers than consumer-facing brands.
Search engine impact
Paid search as we know it disappears or transforms so much that “PPC” no longer applies – there simply aren’t many clicks.
Revenue moves to AI subscriptions, licensing, and sponsored responses.
AI-first companies like OpenAI and Anthropic gain major share unless Google dramatically improves its AI offerings.
What survives
Investigative journalism with strong institutional support, highly specialized publishers with active expert communities, entertainment brands with strong social reach, and commerce-integrated publishing platforms.
Few of these commerce-connected models exist at the necessary scale today, suggesting a major shift in the publishing landscape ahead.
Emerging AI-native revenue models
Traditional web advertising may lose momentum, but new revenue models are already taking shape.
AI platform advertising
As more platforms adopt AI, they’re weaving it directly into their ad systems.
A recent CNN report showed Meta racing to merge its AI chatbot with commercial activity – the headline put it bluntly:
“Meta will soon use your conversations with its AI chatbot to sell you stuff.”
For now, that means AI chats fuel traditional ads. The real question is how long until the model flips and AI becomes the primary advertising engine.
Perplexity also began testing integrated ads in November 2024.
Everyone is rushing to integrate AI with monetization. Who wins is still anyone’s guess.
Dig deeper: Perplexity expands publisher ad revenue sharing program
Content licensing agreements
In May 2024, News Corp signed a deal with OpenAI to bring premium journalism into its models.
It’s one example of a growing trend: major publishers partnering with AI companies to stay relevant.
These deals reflect a simple reality – adapt or fade out.
Beyond traditional models: Large publisher adaptation
ChatGPT has already proved that people will pay for AI subscriptions.
On Nov. 6, 2025, CNBC reported that OpenAI is on track to surpass $20 billion in annualized revenue. Other players, like Anthropic with Claude, are seeing similar traction.
Large publishers with loyal audiences and unique data benefit the most.
They’re using AI to amplify their research, streamline production, and differentiate their content.
Those with proprietary datasets will survive. Those who rely on recycled or syndicated information face a harsh reckoning.
Traditional SEO conditioned publishers to aggregate other people’s data for traffic. In the next era, value-add becomes non-negotiable.
Critics talk about “AI slop,” but much human-produced content has been recycled slop for years. In many ways, AI is forcing the industry to confront a problem it created.
Preparing for an AI-shaped information economy
AI is on a steady path toward becoming the primary way people access information. These shifts unfold over years, but the pace is accelerating.
The countdown has started.
Prepare for an information landscape shaped by AI. Whether we welcome it or not, the transition is underway – and everyone will need to adapt.