A few years ago, searching for information online was simple. You’d open Google, type a question, and click on one of the top links. Maybe it took you to a blog, a news article, or a video. As you consumed the content, ads would load on the page. The deal was unspoken but clear—you got the content for free, and the website earned revenue through those ads.

Today, this process looks very different. Instead of navigating links, you ask an AI assistant. It delivers the answer instantly, with no links, no ads, and no visit to the source. You get what you need in seconds, but the website that created the content doesn’t get your visit—or the ad revenue that once kept it running.

This isn’t just a minor change. It’s a platform shift in how we consume content—and in how it’s monetised.

A Changing Landscape of Content Consumption

For decades, the web relied on a covenant that worked well for everyone: creators published free/subsidised content to attract traffic, advertisers paid for impressions and clicks, and that revenue sustained creators and platforms. Humans were at the center of this ecosystem, engaging with content and indirectly funding it through ad views, primarily via monetised interstitials like banners, clicks, pop-ups, and video ads.

But generative AI has disrupted this dynamic. Instead of sending users to content, AI systems repackage it into quick, seamless answers. This creates cascading challenges:

• Web traffic declines: If users don’t visit the source, creators lose their audience.

• Ads are bypassed: With no visitors, there are no impressions or clicks.

• Revenue evaporate: Creators still power the system but don’t directly share in its value.

It’s not just about the traffic though—it’s also about discovery. For years, creators worked hard to be found. They optimised for search engines like Google, tweaking keywords and building backlinks to climb the rankings. But AI doesn’t work like Google. It doesn’t point people to content; instead, it’s trained or context enriched on massive datasets, often scraped from the web without permission.

Now, there’s a whole new kind of “user” on the web: AI agents, Answer Engines and other Applications. These aren’t humans browsing passively. They’re systems scraping dynamically, pulling information on the fly whenever it’s needed. Take ChatGPT search, for example—these systems query specific content sources in real time to provide more accurate and enriched answers. This means AI isn’t just using pre-trained data anymore; it’s actively pulling from the web in the moment:

Figure 1: OpenAI’s ChatGPT search showing how it browsed and placed in-line attribution for a search query; users have limited incentive to click on the attribution links. Source: ChatGPT

And it’s not only about text. AI systems are consuming everything—images, videos, audio, and more. They blend these formats together to create richer responses, but for creators, the issue remains the same. Their work powers these systems, but they’re not directly benefiting.

Rethinking Monetisation

The traditional monetisation model—content attracts traffic, traffic drives ad impressions, ads fund content—no longer holds up in an AI-driven ecosystem. AI systems consume content silently, without generating monetisable traffic or ad revenue for creators. Some bots operate so aggressively that they overwhelm websites with scraping, bypassing the Robots Exclusion Protocol entirely. The image below, from our AI Bot Analytics Tool, shows the average bot traffic from Answer Engines one of our customers has received.

Figure 2: Valyu’s AI Bot Analytics dashboard showing AI Answer Bot Activity on a website. Source: Valyu.

But this isn’t a dead end. It’s an opportunity to rethink how content creators, advertisers, and AI developers can collaborate to build something better.

Advertisers, for example, can adapt by embedding contextual ads directly into AI interactions. Imagine asking a chatbot for travel advice and receiving personalised recommendations for flights or hotels, complete with booking links. If done right, this kind of advertising wouldn’t feel intrusive; it would feel useful, delivered at the exact moment the user needs it. Importantly, the revenue from such interactions could be shared between the AI developer and the creator whose data powered the recommendation.

For AI developers, there’s a clear opportunity to create tools and systems that ensure creators are compensated. This might include attribution mechanisms that direct users back to original content, licensing frameworks that pay creators for their contributions to AI training or outputs, and discovery tools that help creators remain visible in AI workflows.

These changes wouldn’t just support creators—they’d also make AI systems more transparent and trustworthy.

The Future of Advertising in AI

As Computer Scientists, we are personally excited in the rise of AI agents as decision-makers. These systems won’t just summarise information (”read” only); they’ll soon handle transactions—booking flights, ordering products, or negotiating deals on behalf of users (”write” and “execute”).

For advertisers, this opens up entirely new possibilities. Instead of targeting humans, they can create campaigns aimed at influencing AI-driven decisions. Developers, in turn, can build platforms where agents transact seamlessly, creating new revenue streams through commissions or paid recommendations.

Imagine an AI shopping assistant that compares prices and recommends the best deals—not just based on user preferences but also influenced by sponsored partnerships. Such systems could drive value for everyone involved: advertisers, developers, and creators.

Building the AI-Native Web

The rise of AI isn’t about tearing down the old system; it’s about building a better one. Creators, advertisers, and developers all have a role to play in shaping this new ecosystem.

For creators, it’s about tapping into new monetisation and distribution channels for their content in an AI-native world. For advertisers, it’s an opportunity to evolve with AI-driven consumer behaviour, embedding their messages into new, contextually relevant touch points. For developers, it’s a way to enable richer, more sustainable content ecosystems, inducing transparency and collaboration along the way.

The way we consume content is changing, but that doesn’t mean the web as we know it has to disappear. With the right systems and incentives, we can create an ecosystem where everyone—users, creators, advertisers, and developers—benefits.

This isn’t about fixing what’s broken. It’s about designing this inevitable future together. At Valyu, we’re building the infrastructure to make AI-native content thrive 🛠️.

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Cover image by Google DeepMind from Pexels.