AI Bait Is a Mirage — Here’s How to Get Discovered in the New Age of Search

Key Takeaways

• AI citation bait is outdated & risky: Strategies that once “tricked” AI into citing shallow, stat-stuffed content don’t work in the age of agentic search. 
• Getting cited isn’t enough: Modern AI agents evaluate content in real time, deciding what to trust, summarize, and feature. But mentions alone won’t drive traffic. If your content doesn’t give users a reason to click further, you’ve been cited without impact.
• Human-first content wins in AI search: To show up in agentic search, create content that directly answers user intent, demonstrates experience, and is structured for both users and AI agents.

The launch of agent-based browsing from ChatGPT and Perplexity’s new Comet browser mark a turning point in how AI platforms evaluate and cite content. 

Instead of blindly scraping text, today’s AI systems behave more like humans: Navigating websites, comparing sources, and choosing content based on depth, clarity, and user experience. 

If your content reads like it was written for a machine with short, stat-stuffed paragraphs or rehashed definitions, it’s time to rethink your strategy.

In this article, we’ll break down:

• The rise of agentic discovery 
• Why AI bait falls short
• What agents actually prioritize content 
• How to get your content chosen by AI

From crawled to chosen: The rise of agentic discovery

In the early days of LLMs, “AI bait” — pages designed to be scraped, not read — may have worked. 

This content often includes: 

• Shallow, statistic-stuffed paragraphs 
• Overused jargon meant to impress machines 
• Definition-style explanations that regurgitate common knowledge
• Lack of perspective or originality 
• No clear author or source signals 

While AI bait may have tricked early models, today’s AI systems operate differently. We’ve entered the age of agentic discovery, where tools don’t just surface content. They choose what to trust, summarize, and cite.

Why AI bait is risky: The April Fools’ incident that fooled Google

Here’s a quick example you may have seen earlier this year.

When a Welsh journalist behind the news site Cwmbran Life made up a fake story for April Fools’ Day, he was shocked to see it cited by Google’s AI Overview.

Google’s AI Overview used the satirical article, which claimed the town of Cwmbran has the world’s highest concentration of roundabouts, as the basis for its answer.

While harmless in this case, it’s a clear example of how quickly misinformation can spread when AI systems rely on surface-level signals instead of context and credibility. 

This is exactly the kind of scenario that agentic discovery aims to avoid. Browsing agents and smarter systems are being trained to read between the lines to avoid surfacing content that’s misleading or lacks real-world credibility.

3 ways AI bait falls short in 2025

Here are a few key ways AI bait misses the mark. 

1. Modern AI agents act more like humans

Launched earlier this month, ChatGPT agent and Perplexity’s Comet browser give a glimpse into the future of AI search.

These aren’t just new upgrades. They represent a larger shift in how AI search works on a fundamental level. Rather than simply scraping content, these new systems evaluate and select content similar to how a user would. 

Comet and ChatGPT agents browse the web in real time, weighing context, clarity, and relevance. That means old-school tricks no longer work.

Going forward, the question isn’t, “Can I get cited by AI tools?” Instead, it’s “Would an AI acting on a user’s behalf choose my content?”

2. Citations don’t equal clicks

Remember, just because an AI tool mentions your content doesn’t mean people are visiting your site.

AI responses often paraphrase or summarize what you wrote, strip away the nuance, and deliver it directly in the results, no click required. 

Google’s AI Overviews are a perfect example:

• Sometimes they cite a brand without linking.
• Sometimes they cite a cluster of sites without favoring any one source.
• And sometimes, especially for common knowledge or surface-level content, they don’t cite anyone at all.

According to Pew Research, 88% of AI Overviews cite three or more sources, with only 1% citing a single source.

If your entire strategy hinges on “being a source,” but there’s no reason for the user to dig deeper, you’ve essentially created invisible content with little measurable business value. 

2. It erodes human trust

Content optimized only for AI often reads like it was built in a lab, not written by a subject-matter expert.

Even if AI bait earns a temporary citation, it creates a long-term trust problem. When real users land on the page, whether from a link or through branded search, they’ll skim a few lines, realize there’s nothing valuable, and leave.

Optimizing only for AI citations may result in content that ranks but doesn’t convert, gets paraphrased without credit, and ultimately damages your brand’s credibility.

What AI agents actually prioritize

AI agents don’t just scrape. They’re designed to find fast, clear, trustworthy content that solves users’ problems. 

Here’s what AI agents look for:

AI bait vs. true AI magnet content

Here’s a breakdown that shows, in practice, the difference between AI bait and content that earns AI citations the right way:

Modern agentic platforms reward content designed for humans, not machines. These tactics will help you create content that’s clear, concise, and helpful for users, so you can get discovered by AI and also drive action. 

How to get your content chosen by AI

Let’s break down some practical ways to get your content chosen by AI in the new era of search:

• Focus on helpful, human-centered answers
• Incorporate visuals that support clarity
• Demonstrate human experience with E-E-A-T
• Cite credible data sources (and original research)
• Use schema markup to help AI agents understand content

1. Focus on helpful, human-centered answers

AI agents help users solve problems and complete tasks.

Focus on directly answering search intent, and go beyond surface-level definitions. Answer the user’s question, add context, give an expert perspective beyond what AI traditionally summarizes, and explain why it matters.  

2. Incorporate visuals that support clarity

AI agents are increasingly capable of parsing visual context (like charts or labeled images) and prefer content that enhances user understanding. Custom graphics, screenshots, and tables aren’t just for decoration. They add clarity and create meaningful interactions with users. 

3. Demonstrate human experience with E-E-A-T

E-E-A-T matters more than ever. Cite firsthand knowledge, include author bylines, share original insights, and link to real-world examples. These cues signal trust and authority to both users and AI systems.

4. Cite credible sources (and original research)

Tossing in random stats used to fool early AI models, but not anymore. Use relevant, up-to-date, and properly cited data (bonus if it’s original research). AI agents look for originality and trust signals over filler.

5. Use schema markup to help AI agents understand content

Structured data helps both traditional search engines and AI agents understand your content, not just crawl it. Add FAQ and How-To schema to highlight key information.

Future-proof your content strategy in the new age of AI

Want to make sure your content gets chosen, not just crawled?

WebFX has been optimizing for AI-driven discovery since day one. Whether you’re refreshing existing content or building a human-first strategy from scratch, we can help.

Explore our AI SEO services or contact us online to get started.