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- Tension: Content marketers expected AI search to reward volume and optimization, but the formats earning clicks now demand something far more uncomfortable: genuine expertise and original contribution.
- Noise: The industry’s obsession with predicting AI’s next move has drowned out a simpler truth: the same content principles that always mattered now matter more than ever.
- Direct message: In a world where AI can summarize everything, the content that earns clicks is content that cannot be summarized without losing its essential value.
To learn more about our editorial approach, explore The Direct Message methodology.
The numbers landed like a punch to the gut. A 61% drop in organic click-through rates for queries featuring AI Overviews.
Paid CTRs down 68%. And here’s the part that should unsettle every content marketer who believed they understood the rules: even queries without AI Overviews saw CTRs fall 41%, according to Seer Interactive’s analysis of 25 million impressions.
During my years as a growth strategist at a Fortune 500 tech company, I watched countless algorithm updates shake our strategies. This feels different.
The infrastructure of how people discover content has fundamentally changed, and the response from most of the industry has been predictably reactive: scrambling to “optimize for AI” as if we’re dealing with another technical checkbox to satisfy.
But buried in that same data is something most marketers are missing. Brands cited in AI Overviews earn 35% more organic clicks and 91% more paid clicks than those absent from citations.
The click isn’t dead. It’s selective. It rewards content that AI systems trust enough to reference and that humans find valuable enough to explore further.
The question isn’t whether clicks exist anymore. It’s whether your content deserves them.
The uncomfortable truth about content in the AI era
Here’s what I’ve observed analyzing consumer behavior patterns over the past year: we’re watching a massive sorting mechanism at work. AI Overviews function as a filter that separates content with genuine substance from content designed purely to capture search traffic.
The tension is profound. For nearly two decades, content marketing operated on a relatively simple exchange: create something adequate, optimize it properly, wait for traffic. Now, AI systems are making editorial judgments about which sources deserve citation, and those judgments often favor depth, originality, and verifiable expertise over pure optimization.
Consider the expectation gap. Marketers expected AI search to be another distribution channel to master. Instead, AI has become something closer to a critic, one that synthesizes hundreds of sources and decides which voices carry authority. Search Engine Journal reported that click-through rate reductions range from 34% to 46% when AI summaries appear, yet certain formats consistently break through.
The formats still earning clicks share a common quality: they offer something AI cannot replicate, which is proprietary insight, genuine expertise, practical application, or original data. These aren’t new virtues. They’re the virtues that always defined great content. AI simply made them non-negotiable.
What I’ve found analyzing marketing data is this: the content that struggles most in AI search was already on borrowed time. Generic explainers, thin listicles, surface-level how-tos. AI accelerated their decline, but didn’t cause it.
Where conventional content wisdom misleads us
The noise around AI search has become deafening. Every week brings new predictions about which formats AI will destroy next, which optimization tricks will game the system, which pivot will save your traffic numbers.
This trend-chasing obscures something fundamental: none of the formats that earn clicks in AI search are new. Original research has always performed well. Expert-driven content has always built trust. Practical tools and frameworks have always attracted engaged audiences.
The conventional wisdom says to produce more content optimized specifically for AI citations. This advice misses the point. BrightEdge research found that 89% of citations in AI Overviews come from URLs that aren’t even in the top 10 search rankings. AI systems aren’t rewarding traditional optimization. They’re rewarding content characteristics that optimization alone cannot manufacture.
Another piece of noise: the idea that AI will eventually replace all informational content consumption. The data suggests otherwise. Google reports that clicks from AI Overview results show higher engagement, with users spending more time on site. Users aren’t clicking less because they want less depth. They’re clicking less on content that doesn’t deserve the click.
The media narrative of AI versus human content has created a false dichotomy. The real distinction isn’t format or creator. It’s whether content adds something to the conversation or merely echoes what already exists. AI systems, trained on the entire web, have become remarkably good at identifying the difference.
What actually earns the click
Content that survives AI synthesis is content that loses essential value when reduced to a summary. The click becomes necessary when the insight requires context, the data demands verification, or the application needs demonstration.
Nine formats that demonstrate this principle
1. Original research and proprietary data
When content marketers at WordStream analyzed their AI traffic sources, they discovered something striking: articles based on original statistics accounted for 50% of clicks from AI sources while representing only 5% of clicks from traditional organic search.
AI systems cite data sources because they cannot generate original findings. Users click to verify and explore the underlying methodology.
The format works because proprietary data cannot be summarized without attribution. When someone encounters a citation that reads “according to [your brand’s] research,” they often need the full context to evaluate and apply the finding.
2. Expert commentary with specific credentials
Generic advice floats across thousands of websites. Expert perspective tied to demonstrated experience stands apart. AI systems are increasingly trained to identify and cite content from verifiable subject matter authorities.
This format requires something most brands resist: putting real humans with real credentials behind content. The reluctance is understandable. Experts are scarce, opinionated, and sometimes wrong. But those qualities are precisely what makes their content worth clicking.
3. Interactive tools and calculators
A tool cannot be summarized. When AI mentions that a retirement calculator exists, the user must visit to use it. Interactive content creates functional value that lives beyond any description.
Finance, health, and B2B services have long understood this. The format is now expanding as marketers recognize that utility drives engagement in ways that information alone cannot.
4. Case studies with measurable outcomes
AI can describe what case studies typically contain. It cannot reproduce the specific narrative of how a particular company solved a particular problem with particular results. The specificity is the value.
Effective case studies now require more granular detail than ever. Vague success stories get absorbed into AI summaries. Detailed accounts with verifiable metrics earn the click from readers who want to understand the application.
5. Comparative analysis with clear methodology
Comparison content has always performed well. In the AI era, the methodology matters more than the conclusions. AI can generate comparison tables. It cannot replicate the reasoning behind why certain criteria matter more than others for specific use cases.
The format requires transparency about selection criteria and evaluation process. Readers click when they trust the framework, not merely the results.
6. Video demonstrations and tutorials
Video remains resistant to AI summarization in ways text cannot match. The Surfer SEO AI Citation Report found YouTube dominates citations across multiple industries, representing over 30% of citations in categories like ecommerce and SEO.
The format works because demonstration conveys information that description cannot capture. Showing how something works creates value that persists regardless of how well AI can describe it.
7. Community-driven content and real user perspectives
Reddit’s 450% increase in AI citations between March and June 2025 reveals something significant about what AI systems value: authentic human experience. User-generated perspectives provide the kind of practical, lived insight that corporate content often lacks.
Brands can participate in this dynamic by fostering genuine community discussion, featuring real customer stories, and creating spaces for authentic conversation about their domain.
8. Comprehensive guides with practical frameworks
Long-form content still earns clicks when it provides actionable structure. The key distinction: frameworks people can apply, templates they can adapt, checklists they can follow. AI can describe what a framework accomplishes. Users click when they want to implement it.
The format demands specificity. A guide that offers general principles gets summarized. A guide that offers a step-by-step process with downloadable resources earns the click.
9. Updated benchmarks and industry standards
Recency matters enormously in AI citation. Research indicates AI platforms show strong preference for recently updated content, with some systems ordering references from newest to oldest. Regularly updated benchmarks become recurring citation sources.
This format requires commitment to ongoing maintenance. Annual reports, quarterly updates, and regularly refreshed benchmarks signal both authority and currency to AI systems evaluating source quality.
Building content that earns its place
The formats listed above share a common requirement: investment. Not in optimization tricks or AI gaming strategies, but in the substance of what you’re creating.
Original research costs money. Expert content requires experts. Interactive tools need development resources.
This is the sorting mechanism at work. AI search rewards content that required genuine effort to create because such content provides genuine value when consumed.
The economics of content marketing are shifting from volume toward value, from optimization toward originality.
For practitioners building content strategies in this environment, the path forward starts with an honest assessment.
Which of your current content formats offer something AI cannot replicate? Which simply occupy space that better summaries will absorb?
The nine formats represent starting points. The principle underlying them is more important: create content that loses essential value when reduced to a summary.
Build resources that require interaction to deliver their benefit. Develop insights that demand context to be properly understood.
The click isn’t dead. But it now requires earning.
