I’ve been working in SEO since 2011. There have been plenty of times where industry pros have waxed rhapsodic about how SEO is dying, we’re all out of work, the end is nigh, etc. Of all those, the advent of LLMs is probably the single event that’s changed SEO the most since search engines became a thing at all.
To avoid burying the lede:
You need substantial monthly search volumes in your category, as well as limited established competition, to justify GEO investment.
Organizations already ranking in positions 1-3 for their primary keywords should prioritize conversion optimization over AI citations, while companies struggling to break into page one results may find GEO offers an alternative visibility path. The substantial monthly investment for comprehensive GEO optimization makes it cost-prohibitive unless current organic performance generates insufficient qualified traffic.
AI Overviews – and SERPs where they’re present – drive a fraction of the click-through traffic that traditional organic search results generate. In an industry entirely based around getting people to 1. see and 2. click on the things you produce, it’s been a pretty… exciting couple years.
The Semrush research showing AI search visitors could surpass traditional search visitors by 2028 has led to agencies promising revolutionary GEO results, consultants selling optimization packages, and business leaders wondering whether they’re missing the next big shift.
The reality of AI citations for CTR
The BrightEdge 2025 analysis of AI search behavior documented what every GEO advocate hopes you won’t calculate: Organic search consistently outperforms AI channels for actual conversions. When Google’s AI Overview cites your content, users click through to your site at rates that make traditional organic search look like a traffic firehose by comparison.
A #3 organic ranking generates significantly higher click-through rates than AI citations. Perfect AI citation placement, or being the primary source in an LLM like ChatGPT, drives minimal click-through rates. The fundamental interaction pattern is simply different. Users who feel like they got their answer from the AI interface have less motivation to visit the source than users who see a search snippet and want more detail.
AI interfaces reduce clicks, not generate them.
Even organizations with sophisticated GEO optimization will see traffic volumes from AI citations that represent a fraction of what equivalent traditional search visibility would deliver. The mathematical reality means that even perfect GEO execution reaches a substantially smaller audience than what ranking #3 organically would produce. At the same time, GEO optimization often requires comparable or greater content investment than traditional SEO campaigns.
Google’s official GEO “guidance”
Google’s recently updated AI optimization guidance states unequivocally that “optimizing for generative AI search is optimizing for the search experience, and thus still SEO.”
According to Google, specialized GEO tactics are unnecessary. The same ranking factors that drive search visibility determine AI citations, at least for Google tools. Google’s AI systems rely on the same ranking factors that have determined search visibility for decades. The company that controls the largest AI search integration has told the GEO industry that their specialized optimization techniques are unnecessary overhead.
This guidance reflects how Retrieval Augmented Generation (RAG) systems function under the hood. When ChatGPT, Perplexity, or Google’s AI Overview generates a response, the underlying system first performs a traditional search query to retrieve relevant content, then feeds that content to the language model for synthesis. The retrieval step uses standard search algorithms that prioritize the same authority signals, content quality markers, and technical optimization factors that have always driven organic rankings.
So are we still expected to put in the same amount of SEO effort, but for fewer clicks?
I’m seeing a lot of players in my industry (and all over my LinkedIn feed) repackaging traditional SEO best practices as specialized GEO techniques, often charging premium rates for optimization work that differs minimally from standard content strategy. The semantic markup, structured data implementation, and clear information hierarchy that helps AI systems understand content are identical to the elements that have improved search performance since 2019.
It’s not really clear to me what Google’s end goal is with all this, beyond doing what they can to keep people on Google itself rather than clicking through to other sites.
At the same time, their guidance protects their own business model while potentially misleading content creators about optimization priorities. Traditional search results generate ad revenue through clicks and subsequent searches. If nobody is clicking, where will Google make their money? Certainly via ads in AI search mode, but as we’ve seen people tend not to click stuff inside their AI chat windows.
Where will Google make their money if not by selling ad clicks? That’s like their whole thing.
Brand awareness without revenue is just expensive PR
AI citations generate brand recognition that rarely translates to immediate revenue, which creates a measurement challenge for marketing teams that need to justify optimization spend against quarterly targets.
AI-cited traffic converts at rates 40-60% lower than organic search traffic across most product categories. The conversion gap widens for high-consideration purchases where users research across multiple sessions before making decisions.
Branded Queries
Users who discover brands through AI responses often return later via branded Google searches, which makes GEO investment appear worthless in standard analytics reports since it’s very hard to tell what a user’s previous interactions were.
This delayed conversion pattern means companies may abandon effective GEO strategies before seeing results, while overinvesting in campaigns that generate awareness without purchase intent.
B2B software companies face severe conversion challenges with AI citations because their sales cycles require multiple touchpoints and human interaction before purchase decisions. Enterprise buyers who discover solutions through ChatGPT responses rarely convert directly to trials or demos, instead using AI-gathered information to inform later conversations with sales teams. The lead attribution becomes impossible to track through standard marketing automation systems, making ROI calculations meaningless for B2B GEO campaigns.
Complex service offerings that require customization or integration planning suffer most from the AI citation conversion gap, as users need detailed consultations that AI responses cannot provide.
The measurement disconnect means most GEO budgets function as brand advertising with conversion promises they cannot fulfill.
When pursuing AI citations makes sense
Enterprise software companies selling complex solutions benefit most from GEO investment because buyers conduct extensive research before engaging sales teams, making brand awareness measurably valuable even without direct conversions. Professional services firms like law practices and consulting agencies also see legitimate ROI from AI citations when competing for high-value clients who research extensively before making contact.
In short, the information gain strategy of targeting AI citations works when your company can establish authority on niche topics where AI responses frequently cite the same limited sources.
B2B companies with sales cycles exceeding six months are most likely to find that AI citations correlate with increased inbound inquiries from qualified prospects, even when attribution remains unclear.
The decision framework centers on a simple calculation: If your current organic traffic converts at rates above 2% and generates sufficient qualified leads, GEO investment delays necessary improvements to existing performance. Companies with strong accessibility compliance and structured data implementation often achieve GEO benefits as a byproduct of user experience optimization, making the strategy cost-neutral rather than additive.
The Semrush prediction that AI search visitors could surpass traditional search visitors by 2028 assumes user behavior patterns that may never materialize if conversion rates remain dramatically lower than organic search.
So what can we as marketers control?
As always, creating quality content experiences that serve both human visitors and algorithmic systems (SEO) without compromising either.
References
- Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., & Deshpande, A. (n.d.). GEO: Generative Engine Optimization. https://arxiv.org/pdf/2311.09735
- AI Search Visits Surging in 2025—But Organic Search Remains the Cornerstone of Digital Growth. (2025). BrightEdge. https://www.brightedge.com/resources/research-reports/ai-search-visits-in-surging-2025
- Handley, R. (2025, June 9). We Studied the Impact of AI Search on SEO Traffic. Here’s What We Learned. Semrush Blog; Semrush. https://www.semrush.com/blog/ai-search-seo-traffic-study/
- Rashid, A. B., & Kausik, A. K. (2024). AI Revolutionizing Industries Worldwide: a Comprehensive Overview of Its Diverse Applications. Hybrid Advances, 7(100277), 100277–100277. https://doi.org/10.1016/j.hybadv.2024.100277
- Raulf, C. (2024, May 19). SEO Costs in 2024, & Beyond | A Quick Guide to SEO Pricing. Boulder SEO Marketing – Full-Service SEO and Digital Marketing Agency. https://boulderseomarketing.com/seo-costs-guide-understand-seo-pricing-models/
- Rezazadeh, A., Kohns, M., Bohnsack, R., António, N., & Rita, P. (2025). Generative AI for growth hacking: How startups use generative AI in their growth strategies. Journal of Business Research, 192, 115320. https://doi.org/10.1016/j.jbusres.2025.115320
- Stahl, S. (2024, October 9). B2B Content Marketing Benchmarks, Budgets, and Trends: Outlook for 2025 [Research]. Contentmarketinginstitute.com. https://contentmarketinginstitute.com/b2b-research/b2b-content-marketing-trends-research
- What Generative Search Engines Like and How to Optimize Web Content Cooperatively. (2024). Arxiv.org. https://arxiv.org/html/2510.11438v1
- What Is Generative Engine Optimization (GEO) [Tips & Workflows To Do It]. (2025, May). Moz. https://moz.com/blog/generative-engine-optimization
