AI content has shifted from something fun to play around with into a fundamental component of many brand content strategies. However, in an environment where AI content dominates the internet, the divide between successful content and failed content is widening rapidly.
In addition, as Google continues to develop its AI Overviews and AI-based search experience technologies, it is altering the way users interact with content online. Content ranking alone is simply not enough anymore; instead, brands are realizing that it’s more important than ever to produce content that is credible enough to be cited by AI systems.
In order to get insights into the real happenings at ground zero, we reached out to SEO leaders, founders, marketers, and growth experts and asked two questions:
- What is the worst mistake that brands are making when it comes to producing AI content?
- What works when it comes to getting your content featured in Google’s AI Overviews and AI-generated search results?
The Biggest AI Content Mistakes Brands Are Making
The use of AI technology is increasing the efficiency, cost-effectiveness, and scalability of the content-creation process. But based on our discussions with some experts, most companies commit one common and critical mistake, which is the use of AI to compensate for their lack of expertise.
From drafting unedited AI-generated texts to churning out generic and cookie-cutter content that looks just like those of their competitors, these methods will increase content, but not its quality. Here are some of the mistakes the experts say will hurt rankings and reputation.
Josh Eberly, Chief Marketing Officer, Marygrove
“The biggest mistake that most brands are making today with generative AI is that they are treating it like a magical money printer for their marketing content. They are following the copy-paste routine, not realizing that 100 other companies are using pretty much the same content as them.
The damage is that they are destroying what makes them different from the next guy. It’s simple: if your content sounds and reads the same as your competitors’, then you have become a commodity.”
Key takeaway: AI should amplify differentiation, not eliminate it.
Emma Williams, Founder & CEO, Seene Digital
“The biggest mistake brands are making is using AI to generate content instead of an ideation tool. Gen-AI can’t write original content; prompts from different brands will all produce content built from the same sources, so using it as a set-and-done tool won’t create anything of value.
Without editorial oversight to add lived experience, first-person insights and natural, engaging keyword use, purely gen-AI content won’t meet EEAT criteria and will fail to mesh with your internal linking strategies.”
Key takeaway: Original thinking still matters more than original prompting.
Yevhenii Tymoshenko, CMO, Skylum
“The biggest mistake brands make with content development using AI is relying on the results of LLMs to generate insipid copies of existing material, resulting in identical insights to their peers.
One example came from photography tutorials we tested. AI-generated content produced virtually no traffic because it simply compiled average information from existing online sources.
We flipped the process and used AI-generated outlines only, while adding real-world camera settings, original images, and direct product experience from our team.”
Key takeaway: AI works best as a framework, not the final product.
Teresha Aird, CMO, Custom Neon
“The biggest mistake we see isn’t that brands use AI to write content. It’s that they treat AI output as publishable without conducting any fact-checking.
AI hallucinates plausible details constantly, and a single wrong statistic or invented case study gets amplified across your site. At Custom Neon, we source our own product data, publish manufacturing guidelines, and run customer surveys. We’re handing AI verified facts to structure, not permission to invent.”
Key takeaway: Fact-checking is becoming a competitive advantage
What’s Actually Working in Google AI Overviews?
While mistakes are easy to identify, several contributors shared tactics that are producing measurable results inside AI Overviews and AI-generated search experiences.
A recurring theme emerged: AI systems prefer clarity, structure, direct answers, and unique information.
Mark Bietz, CMO, Halloween Costumes
“The tactic working best for us is building answer-first pages around one clear question with strong intent. AI results favor sources that answer the main question quickly and then build on it with clear context.
If a page tries to answer many questions at once, it becomes weaker for AI retrieval.”
Lesson: One page, one intent.
Sahil Kakkar, CEO & Founder, RankWatch
“One pattern that worked for us was reducing interpretive friction. We stopped publishing pages that mixed education, persuasion, and positioning into one flow.
For one client, this change moved a topic into AI Overview citations within seven weeks. Authority alone did not carry the result. Pages were skipped when claims were buried and difficult to extract.”
Lesson: Make answers easy for machines to understand.
Ruben Medina, Head of Marketing & Sales, Koalendar
“In 2026, the best way to get featured in Google AI Overviews isn’t by creating more content, but by creating more citable content.
Pages with specific data, unique insights, and direct answers receive more visibility than long SEO-driven texts. AI systems prefer verifiable facts, expert opinions, and clear structure.”
Lesson: Create citation-worthy assets.
Lizaveta Piaskova, PR & Content Manager, Innowise
“To be present in Google’s AI Overview, we aim to become a necessary component of the LLM’s knowledge base.
We identify the exact follow-up questions AI search engines generate and build concise, high-density answer blocks to fill those gaps. AI models do not reference generic duplicates. They search for specific values.”
Lesson: Focus on information gain, not content volume.
Victor Karpenko, Founder & CEO, SeoProfy
“We implemented an ‘Answer Block’ method by placing a 50-word block containing only hard data directly below our H1 and H2 headings.
Within 45 days, we saw an 18% to 28% increase in AI Overview inclusion. Google’s LLMs consistently favor immediate, structured responses.”
Lesson: Structure matters as much as expertise.
Jennifer Bagley, CEO, CI Web Group
“What’s moving the needle is zero-click readiness.
AI search pulls from your entire digital footprint, not just your website. Google Business Profile, third-party citations, manufacturer associations, and structured data all contribute to trust signals AI uses when deciding who gets recommended.”
Lesson: AI visibility extends beyond your website.
Khris Steven, Founder, KhrisDigital
“Removing the intro paragraph entirely and opening with the direct answer in sentence one is the change that got our clients into AI Overviews consistently.
We tested this across more than 20 client sites. Six of eight rewritten pages earned AI Overview placements within three weeks.”
Lesson: Lead with the answer.
Jamie Irwin, Founder, Straight Up Search
“The strategy that’s actually moved the needle for me is treating FAQ blocks as the primary AI citation surface.
AI Overviews pull from content that answers questions cleanly in 40-80 words. Clean declarative answers get pulled. Marketing fluff gets ignored.”
Lesson: FAQs are becoming AI citation magnets.
Scott Kasun, Founder, ForeFront Web
“What’s working for us in AI-driven search is depth plus connectivity. We build a strong pillar page and surround it with tightly related supporting content that addresses the full decision journey.
That gives Google more semantic signals and more confidence that your site is a true authority.”
Lesson: Topic clusters still matter in the AI era.
Key Themes Across All Experts
Although contributors came from different industries and markets, their recommendations were remarkably consistent.
The brands winning in AI search are:
- Using AI for ideation and structure, not final publishing
- Adding first-hand expertise and original observations
- Publishing unique data and research
- Fact-checking aggressively
- Creating answer-first content
- Building citation-ready content assets
- Using structured formats that AI can easily extract
- Expanding trust signals beyond their website
The brands struggling with AI content are still focused primarily on scale.
Final Thoughts
The most important takeaway from these experts is that AI has not removed the need for expertise. It has increased the value of it.
AI can help produce content faster than ever before, but speed alone is no longer a competitive advantage. The content winning visibility in Google AI Overviews combines human expertise, structured answers, verifiable facts, and genuine information gain.
As AI search continues to evolve, the brands that thrive will not be those producing the most content. They’ll be the ones producing the most useful, trustworthy, and citable content.
