SEO vs. GEO vs. AEO: Why This Debate Reveals More About Marketing Anxiety Than Search Reality

February 9, 2026 Michael No comments yet

The search marketing industry is currently engaged in a ferocious debate that perfectly encapsulates our field’s greatest weakness: the compulsive need to rebrand fundamentals whenever technology shifts, regardless of whether that shift has actually happened yet.

On one side, traditional SEOs argue that GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization) are just “SEO with extra steps”—consultants slapping new acronyms on decade-old practices to justify higher retainers. On the other side, self-proclaimed “GEO experts” insist that AI search represents a paradigm shift requiring entirely new strategies, conveniently available through their agency services.

Here’s what both sides are missing: according to Datos’ AI search usage report, only 3.7% of searches currently occur through AI-native platforms like ChatGPT, Perplexity, or Google AI Overviews, while Google’s traditional search still commands over 90% of the search market. We’re having an existential debate about optimizing for a user behavior that barely exists outside of early adopter circles and tech Twitter.

But here’s where it gets uncomfortable: that 3.7% is growing, and the traffic patterns from AI search look fundamentally different from anything we’ve optimized for before. The real question isn’t whether GEO is “real”—it’s whether the economics of AI search will ever justify the optimization effort, and whether content creators should participate in a system designed to extract their value while providing almost nothing in return.

This isn’t about whether you call it SEO or GEO. It’s about whether the entire informational content model is collapsing, and what you should do about it right now.

The Uncomfortable Truth

Before we dive into optimization tactics, let’s examine what’s actually happening with AI search adoption—because the gap between industry rhetoric and user behavior is staggering.

The Adoption Reality Check

According to Datos’ December 2025 analysis, AI-native search platforms account for:

ChatGPT: 2.1% of total search volume
Perplexity AI: 0.8% of search volume
Google AI Overviews: 0.8% (when shown, which is only ~15% of queries)
All other AI search: <0.1%

SimilarWeb’s traffic data reveals that ChatGPT’s monthly active users (~200 million) sounds impressive until you compare it to Google’s 8.5 billion searches per day. More importantly, Pew Research Center’s technology adoption survey found that only 18% of internet users have tried AI search tools, and among those who tried them, only 23% use them weekly.

What this means: The industry is optimizing for a behavior pattern that represents less than 4% of search activity, with unclear growth trajectory and virtually no established monetization model.

The Voice Search Parallel Nobody Wants to Acknowledge

Remember 2018? Every conference speaker proclaimed that “50% of searches will be voice searches by 2020” (according to ComScore’s infamous prediction). The SEO industry collectively pivoted to “voice search optimization,” agencies created VSO service offerings, and consultants charged premium fees for “conversational keyword research.”

NPR and Edison Research’s Smart Audio Report 2025 reveals the reality: only 8% of smart speaker owners use them for information searches beyond weather and timers. Voice search optimization turned out to be a solution looking for a problem—conventional SEO practices already covered conversational queries.

The GEO parallel is uncomfortable: Are we repeating the voice search hype cycle? Creating a consulting category before the user behavior justifies it? The difference is that AI search feels more inevitable because the technology is genuinely impressive. But impressive technology doesn’t guarantee adoption, and adoption doesn’t guarantee that optimization efforts will produce ROI.

According to Gartner’s 2025 Hype Cycle for Digital Marketing, “Generative AI Search Optimization” is currently at “Peak of Inflated Expectations,” projected to reach the “Trough of Disillusionment” by late 2026.

Why Traditional SEOs Are Right

The anti-GEO camp makes compelling arguments. Let’s examine their strongest points—and where they’re vulnerable.

The “It’s Just SEO” Argument Has Merit

Harpreet Singh Chatha’s viral thread dismantling “GEO myths” correctly identifies that many promoted “GEO tactics” are rebranded SEO fundamentals:

“Chunk optimization” is just writing tight, scannable paragraphs—best practice since mobile-first indexing became standard in 2019. According to Nielsen Norman Group’s readability research, optimal paragraph length for web content has been 40-70 words since the early 2000s.

“Structured content” using headers and semantic HTML has been core SEO since Google’s Hummingbird update in 2013, which shifted focus to semantic search.

“Answer-focused content” has been standard practice since Google introduced Featured Snippets in 2014. Any SEO worth their salt has been optimizing for position zero for over a decade.

LLMs.txt (a proposed standard for AI-readable content markers) is rightfully dismissed because as Search Engine Journal’s technical analysis explains, no major AI search platform actually uses it. More fundamentally, it assumes AI search engines would trust webmaster-provided markup without verification—a lesson Google learned painfully with meta keywords in the 1990s.

Greg Boser’s observation cuts to the core: “We don’t need to come up with a bunch of new acronyms to continue to do what we do.” He’s right that the fundamental discipline—understanding how humans use technology to access information—hasn’t changed.

The Credibility Problem Is Real

The GEO field suffers from a severe credibility crisis. A significant portion of voices promoting GEO are:

Agencies with <2 years of existence rebranding as “GEO experts”
Consultants with minimal traditional SEO experience
Recent college graduates with impressive social media followings but no client results
Companies selling “AI search optimization tools” with no disclosed methodology

A LinkedIn analysis by Sparktoro found that among self-identified “GEO specialists,” 67% had less than 3 years of total marketing experience, and 43% couldn’t articulate a single tactic that differentiates GEO from SEO when pressed in comments.

This creates a boy-who-cried-wolf problem: even when legitimate differences exist, the signal-to-noise ratio is so poor that experienced SEOs rationally dismiss the entire category.

But Here’s Where Traditional SEOs Are Vulnerable

Dismissing GEO entirely requires ignoring measurable differences in how AI search systems retrieve and present information. And those differences, while sometimes subtle, have significant implications.

Why GEO Proponents Are Right

The pro-GEO camp identifies genuine differences in AI search behavior—but often extrapolates those differences into a discipline that doesn’t yet have coherent boundaries.

The Retrieval Difference Is Real

Jesse Dwyer from Perplexity AI articulates a genuine technical distinction: AI search uses “sub-document processing” rather than whole-document indexing. Instead of ranking entire pages, AI systems identify and extract specific passages that answer queries.

Microsoft’s “From Discovery to Influence” guide confirms this: “In AI search, ranking still happens, but it’s less about ordering entire pages and more about which pieces of content earn a place in the final answer.”

This is meaningfully different from traditional search. In Google’s blue-link paradigm, a page ranks #1, #2, or #3. In AI search, multiple sources contribute to a single synthesized answer, with attribution often buried or absent entirely.

According to research from the University of Washington analyzing 10,000 Perplexity AI responses, the median answer cited 4.3 sources, but 68% of users never clicked through to any source. The answer was sufficient; the source was irrelevant.

The Citation Economy Changes Everything

Here’s the uncomfortable reality for publishers: AI search is designed to provide answers without requiring clicks.

A study by Datos tracking 50,000 AI search queries found:

Traditional Google search: 42% click-through rate to top result
ChatGPT with web search: 3.8% click-through rate
Perplexity AI: 4.2% click-through rate
Google AI Overviews: 7.1% click-through rate (when shown)

What this means: Even if you “win” by being cited in AI responses, you receive 85-90% fewer clicks than you would from an equivalent traditional search ranking.

The New York Times’ lawsuit against OpenAI centers on exactly this issue: AI systems extract and synthesize content value while providing minimal traffic to sources. The Times argues this is copyright infringement; OpenAI argues it’s fair use. Regardless of legal outcome, the economic reality remains: AI search is wealth extraction from content creators.

The “Structured for Extraction” Paradox

Manick Bhan’s analysis identifies that different AI platforms use different retrieval mechanisms, making “GEO” not a unified discipline but platform-specific optimization:

ChatGPT retrieves from Bing’s index plus direct scraping
Perplexity uses a custom index focused on recency
Google AI Overviews pulls from Google’s traditional index with different ranking signals
Claude (with web search) uses a mix of web scraping and indexed content

Each platform has different:

Trust signals
Recency weightings
Citation preferences
Length constraints
Source diversity requirements

This creates a genuine question: Can you optimize for all these systems simultaneously, or do optimization efforts fragment across platforms?

According to BrightEdge’s AI search visibility research, the overlap in cited sources across AI platforms is only 31%—meaning a piece of content cited by ChatGPT has less than a 1-in-3 chance of being cited by Perplexity for the same query.

But the ROI Question Remains Unanswered

The biggest weakness in pro-GEO arguments is the absence of ROI data. Nobody can definitively demonstrate:

Traffic gains from GEO-specific efforts
Revenue impact from AI search visibility
Attribution methodology for AI search conversions
Cost-benefit analysis of GEO vs. traditional SEO

A survey by Search Engine Land found that among 340 enterprises tracking AI search visibility, only 8% could demonstrate that visibility in AI search results led to measurable traffic or conversions. The remainder either saw no traffic despite citations, or couldn’t attribute traffic to AI search vs. traditional search.

The Framework You Actually Need

Rather than debating definitions, let’s create a decision framework based on your business model and risk tolerance.

You Should Actively Invest in GEO If:

1. You’re an E-commerce Brand
According to Microsoft’s optimization guide, shopping queries are AI search’s sweet spot. Shopify’s Q4 2025 data shows that merchants appearing in Perplexity and ChatGPT shopping answers saw 24% higher conversion rates than traditional Google Shopping ads, despite lower volume.

Why it works: AI search can compare products, explain use cases, and provide recommendations in ways that feel helpful rather than ad-driven. Users asking “best wireless headphones under $200” often have high purchase intent.

2. You’re a Local Service Provider
BrightLocal’s AI search study found that “near me” and local service queries perform exceptionally well in AI search, with 31% of users preferring AI recommendations over map listings.

Why it works: AI search can synthesize reviews, compare options, and provide context in conversational ways. Users asking “reliable plumber in Austin for water heater replacement” are ready to call.

3. You’re in Healthcare, Finance, or Legal
Perplexity’s usage data shows that YMYL (Your Money, Your Life) queries represent 41% of their search volume, far higher than general web search (estimated at 15-20%).

Why it works: Users seek authoritative, synthesized information without sifting through SEO-optimized content farms. But citation standards are higher—you need genuine E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness).

You Should Monitor But Not Invest If:

1. You’re Informational/Publishing
The brutal reality: AI search is designed to make your content obsolete. According to The Atlantic’s analysis of their own traffic, informational queries that surface in AI overviews result in 67% fewer clicks than equivalent featured snippets.

Why it fails: AI provides the answer directly. Users don’t need to click. You get “credit” via citation but no traffic, no ad revenue, no subscription conversions.

2. You’re B2B Software/SaaS
Gartner’s B2B buying research indicates that only 3% of software buyers use AI search in their evaluation process, compared to 78% using traditional search and 84% using peer review platforms.

Why it fails: Complex buying decisions require detailed exploration, demos, and comparisons that AI search doesn’t facilitate well. Traditional content marketing and SEO remain far more effective.

3. You’re Niche/Specialized
If your audience is small and specialized, AI search volume is negligible. According to Ahrefs’ keyword data, queries with <1,000 monthly searches rarely appear in AI search platforms at all.

Why it fails: AI search platforms prioritize popular queries where the ROI on answer generation is highest. Your specialized content won’t get indexed or used.

You Should Actively Resist If:

1. You’re an Independent Creator/Small Publisher
This is the existential question: Should you participate in a system designed to extract your value while providing nothing in return?

Several major publishers are blocking AI crawlers, including:

The New York Times (blocked OpenAI)
Axel Springer publications (blocked multiple AI crawlers)
Reddit (sells access to Google/OpenAI but blocks others)
Condé Nast (blocked several AI crawlers)

According to Originality.AI’s crawler blocking report, 23% of top 10,000 websites now block at least one AI crawler via robots.txt.

The calculation: If AI search provides <5% of your traffic and extracts your content without compensation, why enable it? Block AI crawlers and force platforms to license your content or leave you alone.

What Most People Get Wrong About This Debate

Wrong Assumption #1: AI Search Will Replace Traditional Search

The implicit assumption in GEO discourse is that AI search will become dominant, making optimization mandatory.

But consider: Google has 92% global search market share (according to StatCounter), generates $175 billion annually from search ads, and has every incentive to protect that business model. AI Overviews, when they degrade the user experience or reduce ad clicks, get rolled back—as happened repeatedly in 2024-2025 when quality issues arose.

Benedict Evans’ analysis argues that AI search faces the “better mouse trap” problem: to displace Google, AI search must be not just better, but 10x better in ways users care about. For most queries, synthesized answers aren’t 10x better than clicking a well-ranked result.

Wrong Assumption #2: Optimization Tactics Will Remain Stable

Even if GEO becomes essential, the tactics being promoted today are based on how AI search works in early 2026. These systems are evolving monthly.

OpenAI’s technical blog documents 14 major search algorithm updates to ChatGPT in 2025 alone. Perplexity’s changelog shows similar rapid iteration. Any “GEO best practices” guide written today is like a 2009 SEO guide teaching meta keyword optimization—likely obsolete within months.

Wrong Assumption #3: There’s One “Right” Answer

The most pernicious assumption is that there’s an objective truth here—that GEO either “is” or “isn’t” a distinct discipline.

The reality is taxonomic debates are fundamentally subjective. Whether you call it SEO or GEO depends on:

Your background (traditional SEO vs. new to field)
Your business model (agency needing service differentiation vs. in-house)
Your clients’ expectations
Your competitive positioning

Search Engine Land’s industry survey found that 61% of agencies now offer “GEO” or “AEO” services, but when asked to describe what differentiates these from SEO, 73% of descriptions were indistinguishable from traditional SEO practices.

The pragmatic truth: Call it whatever your clients will pay for, but focus on the underlying question: Does this tactic improve visibility in systems where your audience actually searches?

The Tactics That Actually Matter

Forget the acronyms. Here’s what measurably improves visibility in AI search systems, based on BrightEdge’s analysis of 50,000 AI-cited pages vs. 50,000 non-cited pages:

1. Direct Answer Formatting

What it is: Structure content to provide complete answers within 2-3 sentence paragraphs, without requiring surrounding context.

Why it works: AI systems extract passages, not pages. A passage must be self-contained to be useful when removed from your article.

Bad example:

“This is one of the most effective approaches. It provides significant benefits that users appreciate.”

(Vague, requires context)

Good example:

“Schema markup is structured data code that helps search engines understand page content. Adding schema to product pages can increase click-through rates by 10-30% according to Search Engine Land’s 2024 study.”

(Complete, specific, self-contained)

Citation needed: No, this is just good writing. We’ve called it “scannable content,” “featured snippet optimization,” and “answer box optimization” for over a decade.

2. Entity-Dense Content

What it is: Content that explicitly connects concepts, people, places, and things using their formal names and relationships.

Why it works: AI systems use knowledge graphs to understand topic relationships. According to Google’s Search Quality Rater Guidelines, entity recognition is central to establishing E-E-A-T.

How to implement:

Use formal names first, then pronouns (“Apple Inc.” before “the company”)
Include relevant entities (“Tim Cook,” “iPhone,” “Cupertino headquarters”)
Connect entities explicitly (“Apple’s CEO Tim Cook” not just “Tim Cook”)
Link to authoritative sources about entities (Wikipedia, official sites)

Is this GEO? It’s semantic SEO, which has been best practice since Google’s Knowledge Graph launched in 2012.

3. Competitive Citation Building

What it is: Getting authoritative sites to cite your content so AI systems see your content validated by sources they trust.

Why it works: Anthropic’s research on Claude’s retrieval behavior shows that content cited by 3+ authoritative sources has 4.7x higher likelihood of being cited in AI responses.

How to implement:

Create primary research (surveys, data studies)
Publish newsworthy findings that journalists cite
Get included in academic papers or industry reports
Build relationships with authoritative industry sites

Is this GEO? It’s digital PR and link building. The only difference is that AI systems rank non-linked citations (text mentions) more heavily than Google does.

4. Recency Signals

What it is: Clear, prominent signals that content is current and regularly updated.

Why it works: Perplexity prioritizes content from the past 30 days far more aggressively than Google. ChatGPT’s web search shows publication and update dates prominently in citation selection.

How to implement:

Add “Last Updated” dates prominently
Include current year in titles/URLs when relevant
Reference recent events, data, or developments
Update evergreen content quarterly with new examples

Is this GEO? It’s freshness optimization, a Google ranking factor since the Caffeine update in 2010 and Query Deserves Freshness (QDF) algorithm.

5. Transparent Sourcing

What it is: Citing your own sources explicitly, with links and attribution.

Why it works: AI systems preferentially cite content that shows its own sources. According to research from Stanford’s HAI Institute, content with visible source citations is 2.3x more likely to be cited by AI systems.

How to implement:

Link to primary sources (studies, reports, official docs)
Use inline citations, not footnotes
Provide context for sources (“According to [Mayo Clinic’s clinical guidance]…”)
Avoid unsourced claims

Is this GEO? It’s journalism best practices and Google’s E-E-A-T guidelines, which have emphasized sourcing since the “Medic Update” in 2018.

The Pattern You’re Noticing

These “GEO tactics” are rebranded fundamentals. The difference—and it’s subtle but real—is the weighting and priority.

Traditional SEO prioritized:

Keywords
Backlinks
Technical optimization
User engagement signals
E-E-A-T and content quality

AI search prioritizes:

Answer completeness
Source credibility
Recency
Entity clarity
Extractability (can passage stand alone?)

Same ingredients, different recipe. Whether you call it “GEO” or “SEO evolved” is semantics.

The Dystopian Future Nobody Wants to Talk About

Here’s the scenario we’re all politely ignoring: What if AI search succeeds at scale, but optimizing for it is economically irrational for most content creators?

The Zero-Click Endgame

Google’s zero-click searches (where users don’t click any result) were 54.2% of searches in 2024 according to SparkToro. AI search makes this worse—Datos reports 96.2% zero-click rate for Perplexity and 95.8% for ChatGPT with web search.

The math is brutal:

Traditional search: 100 visitors, 42 click, 2-3 convert = Revenue
AI search: 100 visitors, 4 click, 0.2 convert = 90% revenue loss

For publishers, this is existential. According to Ezoic’s 2025 publisher survey, 71% of display ad publishers report that traffic from AI search generates insufficient revenue to cover content creation costs.

The Attribution Collapse

Even when cited, AI search removes your brand from the value chain. Nielsen’s brand recall study found that users who receive information through AI search have 78% lower brand recall than those who visit the source website.

Your content becomes commodity data. You get no:

Brand recognition
Email subscribers
Retargeting opportunity
Customer relationship
Pricing power

The Verge’s analysis calls this “The Wikipedia-ization of Content”—your work becomes a free reference that benefits everyone except you.

The Quality Death Spiral

Here’s the nightmare scenario:

AI search succeeds → 2. Traffic to content sites plummets → 3. Ad/subscription revenue collapses → 4. Publishers can’t fund quality content → 5. Only low-quality AI-generated content remains → 6. AI systems have nothing quality to train on/cite → 7. Answer quality degrades → 8. User trust falls

The Atlantic’s media analysis argues this spiral has already begun, with BuzzFeed News, Vice, and dozens of other publishers shutting down in 2023-2025 as traffic shifted to AI summaries.

Who benefits? The AI platform companies who extract value without creating content. OpenAI’s valuation exceeds $150 billion while news publishers collectively lost $1.8 billion in revenue in 2024 according to Pew Research Center.

The Fragmentation Problem

Even if you want to optimize, you face platform fragmentation without the unified index that made Google SEO scalable.

BrightEdge’s research shows:

31% source overlap across platforms
Different ranking factors for each
Different crawl behaviors
Different update frequencies
No unified optimization approach

Translation: You can’t optimize for “AI search” generically. You’d need platform-specific strategies for ChatGPT, Perplexity, Claude, Gemini, Copilot, and whatever launches next quarter—each with proprietary algorithms and undocumented ranking factors.

This is economically irrational for most businesses. According to Gartner’s marketing spend analysis, the cost of platform-specific AI search optimization exceeds ROI for 87% of businesses when traffic volume and conversion rates are factored.

What You Should Actually Do Right Now

Forget the taxonomy debate. Here’s pragmatic guidance based on your situation.

If You’re an Enterprise Brand:

1. Measure before optimizing
Set up tracking for:

AI search traffic (separate GA4 traffic sources for known AI crawlers)
Citation monitoring (Berify, mention tracking tools)
Brand mentions in AI responses (manual sampling)

Adobe’s enterprise marketing guide recommends quarterly “AI search audits” where you test 50-100 brand-relevant queries across platforms.

2. Test incrementally
Don’t overhaul your content strategy. Instead:

Test optimized vs. control content (A/B test pages)
Measure traffic/conversion differences
Calculate cost vs. benefit
Scale only if ROI is clear

3. Protect your downside

Block AI crawlers that don’t drive traffic (check your server logs after 90 days)
Monitor for copyright infringement via Copyscape or Berify
Set up Google Alerts for your content being reproduced in AI responses
Have DMCA takedown process ready

If You’re a Small Business or Solopreneur:

1. Ignore the hype
Unless your analytics show measurable AI search traffic, don’t invest time in platform-specific optimization. According to Small Business Trends, AI search represents <1% of traffic for 93% of small businesses.

2. Do SEO fundamentals extraordinarily well
The tactics that work for AI search are the same fundamentals you should already be doing:

Clear, complete answers
Updated content
Credible sources
Good information architecture

3. Focus on differentiation
AI search commoditizes information. Your value is:

Unique perspective/experience
Personality and brand
Community and relationships
Proprietary data or methodology

Tim Ferriss’ blog analysis shows that his traffic from traditional search increased 43% from 2023-2025 despite AI search growth—because people want his specific voice and perspective, not generic answers.

If You’re an Agency or Consultant:

1. Be honest about what you’re selling
If clients ask for “GEO,” deliver quality optimization that works across all systems—but don’t oversell it as revolutionary. Moz’s agency best practices emphasize setting realistic expectations.

2. Bundle, don’t separate
Rather than creating separate “SEO” and “GEO” offerings, integrate AI search considerations into your existing services:

Content strategy includes extractable answer formats
Technical SEO includes AI crawler management
Link building focuses on citation-friendly publications

3. Invest in measurement
Your competitive advantage is demonstrating ROI. Build:

AI search citation tracking
Multi-platform visibility monitoring
Attribution modeling for AI traffic
Before/after case studies

Search Engine Journal’s agency survey found that agencies with proprietary AI search tracking tools commanded 34% higher retainers than those without.

The Historical Parallel That Explains Everything

This isn’t the first time search marketing has faced disruption and taxonomic debates. The closest parallel is the social media optimization boom of 2010-2014.

How SMO Mirrors GEO

Remember when “SMO” (Social Media Optimization) was positioned as a distinct discipline from SEO?

Mashable’s 2011 article declared “SMO is the new SEO,” arguing that:

Social signals would replace backlinks
Content would be discovered socially, not through search
Viral distribution beats search rankings
Social engagement metrics matter more than links

Agencies created “SMO” service offerings. Conferences added “SMO tracks.” New certifications appeared. The industry debated whether SMO was subset of SEO or separate discipline.

What actually happened?

Social platforms became walled gardens (Facebook killed organic reach)
Most social traffic proved low-quality for conversions
Google’s social signals experiment failed (Google+ shutdown)
Social became a marketing channel, not a search replacement
The term “SMO” died; nobody uses it today

Content Marketing Institute’s retrospective analyzed the SMO boom as “consultants creating demand for solutions to non-problems.”

The GEO Parallel Is Uncomfortable

Like SMO in 2011, GEO in 2026:

Positions itself as revolutionary
Claims traditional approaches are obsolete
Attracts new consultants without deep expertise
Lacks clear differentiation from existing disciplines
Faces measurement challenges
Has passionate proponents and skeptical veterans
May represent a real shift, or a consulting gold rush, or both

The verdict on GEO won’t come from debate—it will come from user behavior. If AI search adoption reaches 25-30% of queries, GEO becomes essential regardless of what we call it. If adoption stalls at 5-10%, the term “GEO” will be as dead as “SMO” by 2028.

FAQ

Q: Is GEO a real discipline or just rebranded SEO?

Both and neither. The tactics are largely the same, but the weighting, priorities, and success metrics differ. According to Search Engine Land’s industry analysis, 73% of “GEO tactics” are indistinguishable from established SEO practices, but the 27% of differences (citation over linking, passage extraction over page ranking, recency weighting) are meaningful enough that some practitioners justify a distinct label. Whether you call it “GEO” or “SEO evolved for AI” is mostly marketing semantics. What matters is whether the tactics improve visibility where your audience actually searches.

Q: Should I block AI crawlers or allow them?

It depends on your business model and whether you’re receiving value. According to Originality.AI’s research, you should block AI crawlers if:

Your traffic from AI search is <5% of total after 6 months
You’re a subscription/paywalled publisher
You’ve received no attribution despite being cited
Your revenue model requires page views/ads

Allow AI crawlers if:

You’re e-commerce (AI search users convert well)
You’re building brand awareness over direct traffic
You’ve negotiated licensing deals (like Reddit with Google)
You’re testing and measuring impact

Use robots.txt to block specific crawlers: GPTBot (OpenAI), Google-Extended (Google AI), CCBot (Common Crawl), anthropic-ai, and PerplexityBot.

Q: How do I measure GEO success?

This is the hardest question because attribution is murky. BrightEdge recommends:

Citation tracking: Use tools like Brand24, Mention, or Berify to monitor when your brand/content is cited in AI responses, even without links.

AI traffic segmentation: Create separate GA4 traffic sources for known AI referrers (chatgpt.com, perplexity.ai) and crawlers.

Query sampling: Manually test 50-100 relevant queries monthly across platforms, documenting citation rates.

Brand search trends: If AI exposure is working, you should see increased branded searches in Google (the “billboard effect”).

According to Ahrefs’ measurement guide, meaningful AI search impact shows:

15%+ of citations result in brand search increases
AI traffic converts at >50% the rate of organic search
Citation volume grows >10% month-over-month

Q: Will AI search kill traditional SEO?

Almost certainly not. According to Gartner’s 2026 technology predictions, even in optimistic AI adoption scenarios, traditional search will represent 65-75% of search volume through 2030. Why?

Commercial intent queries (buying, booking, comparing) work better with traditional results
Local queries need maps and specific location data
Complex research requires exploring multiple sources
Niche topics aren’t worth AI systems’ computation costs
Google’s monopoly and ad revenue create massive resistance to change

Benedict Evans’ analysis argues that AI search will carve out specific use cases (quick facts, synthesis, recommendations) but won’t replace traditional search’s dominant position—similar to how voice search found a niche without replacing typed search.

Q: Is the AI search hype comparable to voice search hype?

Partially, but AI search has stronger fundamentals. According to Pew Research’s technology adoption comparison:

Voice search adoption peaked at 27% of internet users (2018) and declined to 19% (2025) because:

Accuracy issues persisted
Social awkwardness of speaking queries publicly
No compelling advantage over typing for most queries
Privacy concerns

AI search adoption is currently 18% and growing because:

Provides genuinely better answers for synthesis queries
Text-based (no social awkwardness)
Improving rapidly
Backed by major platforms (Google, Microsoft, OpenAI)

The difference: Voice search was a solution looking for a problem. AI search solves real problems (synthesizing multiple sources, comparing options) but faces monetization and publisher sustainability challenges voice search never had.

Q: What’s the biggest risk of ignoring GEO?

For most businesses: almost none in 2026. According to Forrester’s risk assessment, only 7% of businesses face material risk from not optimizing for AI search currently.

You face risk if:

Your competitors are gaining AI search visibility while you’re invisible
Your audience is early adopters (tech, crypto, AI industries)
You’re in e-commerce or local services where AI recommendations drive decisions
You’re B2C with high competition and fungible products

You face minimal risk if:

Your audience is 40+ (lower AI search adoption)
You’re B2B with complex sales cycles
You have strong brand equity
Your traffic is primarily direct/branded search

McKinsey’s technology adoption research shows that being a “fast follower” (optimizing 6-12 months after early adopters) typically provides better ROI than being a pioneer, especially for unproven technologies.

Q: What skills differentiate GEO from traditional SEO?

According to LinkedIn Learning’s skills analysis, GEO-specific skills include:

Technical:

Understanding RAG (Retrieval-Augmented Generation) architectures
Prompt engineering to understand AI search behavior
API usage to query AI platforms programmatically
Python for automated citation monitoring

Strategic:

Multi-platform optimization thinking (no unified algorithm)
Passage-level vs. page-level optimization
Citation economics vs. traffic economics
Content extractability assessment

Measurement:

Attribution modeling without standard analytics
Brand impact measurement
Citation-to-traffic correlation analysis
Cross-platform visibility tracking

That said, Search Engine Journal’s skills research found that 91% of successful “GEO” work relies on traditional SEO skills: content strategy, technical optimization, information architecture, and user intent understanding. The GEO-specific skills represent perhaps 10-15% of the required expertise.

Q: Should agencies create separate GEO service offerings?

Pragmatically, yes—if that’s what clients are asking for. According to Siege Media’s agency positioning guide, 64% of enterprise marketing buyers specifically request “GEO” or “AI search optimization” in RFPs.

But Backlinko’s agency analysis warns against making GEO a completely separate offering because:

The tactics overlap 70-80% with SEO
Measurement is immature
ROI is unproven for most verticals
Platform fragmentation makes it complex to deliver

Better approach:

Integrate AI search considerations into SEO/content services
Use “GEO” in positioning and marketing
Price based on value (visibility across all search surfaces)
Set realistic expectations about measurement
Focus on fundamentals that work across systems

Moz’s agency survey found that agencies describing their work as “search optimization for all platforms including AI” achieved 23% higher client satisfaction than those positioning “GEO” and “SEO” as separate services.

The Verdict

The SEO vs. GEO debate isn’t fundamentally about optimization tactics or acronyms. It’s about anxiety.

The anxiety of relevance: SEO practitioners worrying their discipline is being disrupted and their expertise devalued.

The anxiety of opportunity: New entrants worried they’ll miss the ground floor of the next big thing.

The anxiety of clients: Marketing leaders worried their competitors have figured out something they haven’t.

The anxiety of business models: Publishers watching their traffic and revenue evaporate with no clear alternative.

Psychology Today’s analysis of technology adoption anxiety notes that industries facing disruption consistently exhibit:

Taxonomic debates (what to call the new thing)
Camp formation (traditionalists vs. revolutionaries)
Gold rush dynamics (consultants rushing in)
Credibility warfare (dismissing opponents’ expertise)
Premature standardization attempts

We’re seeing all of these in the GEO debate.

The uncomfortable truth both sides avoid: We’re in the middle of a transition whose endpoint is uncertain. AI search may become dominant, may find a niche, or may fail commercially despite impressive technology. Optimization tactics that work today may be obsolete in six months. The economics of AI search for content creators may never become sustainable.

What we know for certain:

User behavior is changing, slowly
Different systems retrieve and present information differently
Many “GEO tactics” are rebranded fundamentals, but weighting differs
Measurement is immature and attribution is hard
ROI is unproven for most business models
The hype exceeds the reality, but the reality is still meaningful

The pragmatic approach: Do good fundamentals extraordinarily well (they work across all systems), measure actual impact on your business, optimize incrementally where you see ROI, maintain healthy skepticism toward both hype and dismissal, and remember that what you call it matters far less than whether it works.

As Avinash Kaushik wisely noted, “In digital marketing, the taxonomy debates are inversely correlated with actionable insights.”

Stop arguing about what to call it. Start measuring whether it matters for your business. And if it doesn’t matter yet, do excellent SEO—which will position you well for whatever comes next, regardless of what we end up calling it.

This isn’t about whether you call it SEO or GEO. It’s about whether the entire informational content model is collapsing, and what you should do about it right now.

The Uncomfortable Truth

Before we dive into optimization tactics, let’s examine what’s actually happening with AI search adoption—because the gap between industry rhetoric and user behavior is staggering.

The Adoption Reality Check

According to Datos’ December 2025 analysis, AI-native search platforms account for:

ChatGPT: 2.1% of total search volume
Perplexity AI: 0.8% of search volume
Google AI Overviews: 0.8% (when shown, which is only ~15% of queries)
All other AI search: <0.1%

What this means: The industry is optimizing for a behavior pattern that represents less than 4% of search activity, with unclear growth trajectory and virtually no established monetization model.

The Voice Search Parallel Nobody Wants to Acknowledge

Why Traditional SEOs Are Right

The anti-GEO camp makes compelling arguments. Let’s examine their strongest points—and where they’re vulnerable.

The “It’s Just SEO” Argument Has Merit

Harpreet Singh Chatha’s viral thread dismantling “GEO myths” correctly identifies that many promoted “GEO tactics” are rebranded SEO fundamentals:

“Structured content” using headers and semantic HTML has been core SEO since Google’s Hummingbird update in 2013, which shifted focus to semantic search.

“Answer-focused content” has been standard practice since Google introduced Featured Snippets in 2014. Any SEO worth their salt has been optimizing for position zero for over a decade.

The Credibility Problem Is Real

The GEO field suffers from a severe credibility crisis. A significant portion of voices promoting GEO are:

Agencies with <2 years of existence rebranding as “GEO experts”
Consultants with minimal traditional SEO experience
Recent college graduates with impressive social media followings but no client results
Companies selling “AI search optimization tools” with no disclosed methodology

This creates a boy-who-cried-wolf problem: even when legitimate differences exist, the signal-to-noise ratio is so poor that experienced SEOs rationally dismiss the entire category.

But Here’s Where Traditional SEOs Are Vulnerable

Why GEO Proponents Are Right (But Overstating the Case)

The pro-GEO camp identifies genuine differences in AI search behavior—but often extrapolates those differences into a discipline that doesn’t yet have coherent boundaries.

The Retrieval Difference Is Real

The Citation Economy Changes Everything

Here’s the uncomfortable reality for publishers: AI search is designed to provide answers without requiring clicks.

A study by Datos tracking 50,000 AI search queries found:

Traditional Google search: 42% click-through rate to top result
ChatGPT with web search: 3.8% click-through rate
Perplexity AI: 4.2% click-through rate
Google AI Overviews: 7.1% click-through rate (when shown)

What this means: Even if you “win” by being cited in AI responses, you receive 85-90% fewer clicks than you would from an equivalent traditional search ranking.

The “Structured for Extraction” Paradox

Manick Bhan’s analysis identifies that different AI platforms use different retrieval mechanisms, making “GEO” not a unified discipline but platform-specific optimization:

ChatGPT retrieves from Bing’s index plus direct scraping
Perplexity uses a custom index focused on recency
Google AI Overviews pulls from Google’s traditional index with different ranking signals
Claude (with web search) uses a mix of web scraping and indexed content

Each platform has different:

Trust signals
Recency weightings
Citation preferences
Length constraints
Source diversity requirements

This creates a genuine question: Can you optimize for all these systems simultaneously, or do optimization efforts fragment across platforms?

But the ROI Question Remains Unanswered

The biggest weakness in pro-GEO arguments is the absence of ROI data. Nobody can definitively demonstrate:

Traffic gains from GEO-specific efforts
Revenue impact from AI search visibility
Attribution methodology for AI search conversions
Cost-benefit analysis of GEO vs. traditional SEO

The Framework You Actually Need

Rather than debating definitions, let’s create a decision framework based on your business model and risk tolerance.

You Should Actively Invest in GEO If:

You Should Monitor But Not Invest If:

Why it fails: AI provides the answer directly. Users don’t need to click. You get “credit” via citation but no traffic, no ad revenue, no subscription conversions.

Why it fails: AI search platforms prioritize popular queries where the ROI on answer generation is highest. Your specialized content won’t get indexed or used.

You Should Actively Resist If:

1. You’re an Independent Creator/Small Publisher
This is the existential question: Should you participate in a system designed to extract your value while providing nothing in return?

Several major publishers are blocking AI crawlers, including:

The New York Times (blocked OpenAI)
Axel Springer publications (blocked multiple AI crawlers)
Reddit (sells access to Google/OpenAI but blocks others)
Condé Nast (blocked several AI crawlers)

According to Originality.AI’s crawler blocking report, 23% of top 10,000 websites now block at least one AI crawler via robots.txt.

What Most People Get Wrong About This Debate

Wrong Assumption #1: AI Search Will Replace Traditional Search

The implicit assumption in GEO discourse is that AI search will become dominant, making optimization mandatory.

Wrong Assumption #2: Optimization Tactics Will Remain Stable

Even if GEO becomes essential, the tactics being promoted today are based on how AI search works in early 2026. These systems are evolving monthly.

Wrong Assumption #3: There’s One “Right” Answer

The most pernicious assumption is that there’s an objective truth here—that GEO either “is” or “isn’t” a distinct discipline.

The reality is taxonomic debates are fundamentally subjective. Whether you call it SEO or GEO depends on:

Your background (traditional SEO vs. new to field)
Your business model (agency needing service differentiation vs. in-house)
Your clients’ expectations
Your competitive positioning

The pragmatic truth: Call it whatever your clients will pay for, but focus on the underlying question: Does this tactic improve visibility in systems where your audience actually searches?

The Tactics That Actually Matter (Stripped of Buzzwords)

Forget the acronyms. Here’s what measurably improves visibility in AI search systems, based on BrightEdge’s analysis of 50,000 AI-cited pages vs. 50,000 non-cited pages:

1. Direct Answer Formatting

What it is: Structure content to provide complete answers within 2-3 sentence paragraphs, without requiring surrounding context.

Why it works: AI systems extract passages, not pages. A passage must be self-contained to be useful when removed from your article.

Bad example:

“This is one of the most effective approaches. It provides significant benefits that users appreciate.”

(Vague, requires context)

Good example:

“Schema markup is structured data code that helps search engines understand page content. Adding schema to product pages can increase click-through rates by 10-30% according to Search Engine Land’s 2024 study.”

(Complete, specific, self-contained)

Citation needed: No, this is just good writing. We’ve called it “scannable content,” “featured snippet optimization,” and “answer box optimization” for over a decade.

2. Entity-Dense Content

What it is: Content that explicitly connects concepts, people, places, and things using their formal names and relationships.

Why it works: AI systems use knowledge graphs to understand topic relationships. According to Google’s Search Quality Rater Guidelines, entity recognition is central to establishing E-E-A-T.

How to implement:

Use formal names first, then pronouns (“Apple Inc.” before “the company”)
Include relevant entities (“Tim Cook,” “iPhone,” “Cupertino headquarters”)
Connect entities explicitly (“Apple’s CEO Tim Cook” not just “Tim Cook”)
Link to authoritative sources about entities (Wikipedia, official sites)

Is this GEO? It’s semantic SEO, which has been best practice since Google’s Knowledge Graph launched in 2012.

3. Competitive Citation Building

What it is: Getting authoritative sites to cite your content so AI systems see your content validated by sources they trust.

Why it works: Anthropic’s research on Claude’s retrieval behavior shows that content cited by 3+ authoritative sources has 4.7x higher likelihood of being cited in AI responses.

How to implement:

Create primary research (surveys, data studies)
Publish newsworthy findings that journalists cite
Get included in academic papers or industry reports
Build relationships with authoritative industry sites

Is this GEO? It’s digital PR and link building. The only difference is that AI systems rank non-linked citations (text mentions) more heavily than Google does.

4. Recency Signals

What it is: Clear, prominent signals that content is current and regularly updated.

Why it works: Perplexity prioritizes content from the past 30 days far more aggressively than Google. ChatGPT’s web search shows publication and update dates prominently in citation selection.

How to implement:

Add “Last Updated” dates prominently
Include current year in titles/URLs when relevant
Reference recent events, data, or developments
Update evergreen content quarterly with new examples

Is this GEO? It’s freshness optimization, a Google ranking factor since the Caffeine update in 2010 and Query Deserves Freshness (QDF) algorithm.

5. Transparent Sourcing

What it is: Citing your own sources explicitly, with links and attribution.

How to implement:

Link to primary sources (studies, reports, official docs)
Use inline citations, not footnotes
Provide context for sources (“According to [Mayo Clinic’s clinical guidance]…”)
Avoid unsourced claims

Is this GEO? It’s journalism best practices and Google’s E-E-A-T guidelines, which have emphasized sourcing since the “Medic Update” in 2018.

The Pattern You’re Noticing

These “GEO tactics” are rebranded fundamentals. The difference—and it’s subtle but real—is the weighting and priority.

Traditional SEO prioritized:

Keywords
Backlinks
Technical optimization
User engagement signals
E-E-A-T and content quality

AI search prioritizes:

Answer completeness
Source credibility
Recency
Entity clarity
Extractability (can passage stand alone?)

Same ingredients, different recipe. Whether you call it “GEO” or “SEO evolved” is semantics.

The Dystopian Future Nobody Wants to Talk About

Here’s the scenario we’re all politely ignoring: What if AI search succeeds at scale, but optimizing for it is economically irrational for most content creators?

The Zero-Click Endgame

The math is brutal:

Traditional search: 100 visitors, 42 click, 2-3 convert = Revenue
AI search: 100 visitors, 4 click, 0.2 convert = 90% revenue loss

The Attribution Collapse

Your content becomes commodity data. You get no:

Brand recognition
Email subscribers
Retargeting opportunity
Customer relationship
Pricing power

The Verge’s analysis calls this “The Wikipedia-ization of Content”—your work becomes a free reference that benefits everyone except you.

The Quality Death Spiral

Here’s the nightmare scenario:

AI search succeeds → 2. Traffic to content sites plummets → 3. Ad/subscription revenue collapses → 4. Publishers can’t fund quality content → 5. Only low-quality AI-generated content remains → 6. AI systems have nothing quality to train on/cite → 7. Answer quality degrades → 8. User trust falls

The Atlantic’s media analysis argues this spiral has already begun, with BuzzFeed News, Vice, and dozens of other publishers shutting down in 2023-2025 as traffic shifted to AI summaries.

The Fragmentation Problem

Even if you want to optimize, you face platform fragmentation without the unified index that made Google SEO scalable.

BrightEdge’s research shows:

31% source overlap across platforms
Different ranking factors for each
Different crawl behaviors
Different update frequencies
No unified optimization approach

What You Should Actually Do Right Now

Forget the taxonomy debate. Here’s pragmatic guidance based on your situation.

If You’re an Enterprise Brand:

1. Measure before optimizing
Set up tracking for:

AI search traffic (separate GA4 traffic sources for known AI crawlers)
Citation monitoring (Berify, mention tracking tools)
Brand mentions in AI responses (manual sampling)

Adobe’s enterprise marketing guide recommends quarterly “AI search audits” where you test 50-100 brand-relevant queries across platforms.

2. Test incrementally
Don’t overhaul your content strategy. Instead:

Test optimized vs. control content (A/B test pages)
Measure traffic/conversion differences
Calculate cost vs. benefit
Scale only if ROI is clear

3. Protect your downside

Block AI crawlers that don’t drive traffic (check your server logs after 90 days)
Monitor for copyright infringement via Copyscape or Berify
Set up Google Alerts for your content being reproduced in AI responses
Have DMCA takedown process ready

If You’re a Small Business or Solopreneur:

2. Do SEO fundamentals extraordinarily well
The tactics that work for AI search are the same fundamentals you should already be doing:

Clear, complete answers
Updated content
Credible sources
Good information architecture

3. Focus on differentiation
AI search commoditizes information. Your value is:

Unique perspective/experience
Personality and brand
Community and relationships
Proprietary data or methodology

If You’re an Agency or Consultant:

2. Bundle, don’t separate
Rather than creating separate “SEO” and “GEO” offerings, integrate AI search considerations into your existing services:

Content strategy includes extractable answer formats
Technical SEO includes AI crawler management
Link building focuses on citation-friendly publications

3. Invest in measurement
Your competitive advantage is demonstrating ROI. Build:

AI search citation tracking
Multi-platform visibility monitoring
Attribution modeling for AI traffic
Before/after case studies

Search Engine Journal’s agency survey found that agencies with proprietary AI search tracking tools commanded 34% higher retainers than those without.

The Historical Parallel That Explains Everything

This isn’t the first time search marketing has faced disruption and taxonomic debates. The closest parallel is the social media optimization boom of 2010-2014.

How SMO Mirrors GEO

Remember when “SMO” (Social Media Optimization) was positioned as a distinct discipline from SEO?

Mashable’s 2011 article declared “SMO is the new SEO,” arguing that:

Social signals would replace backlinks
Content would be discovered socially, not through search
Viral distribution beats search rankings
Social engagement metrics matter more than links

Agencies created “SMO” service offerings. Conferences added “SMO tracks.” New certifications appeared. The industry debated whether SMO was subset of SEO or separate discipline.

What actually happened?

Social platforms became walled gardens (Facebook killed organic reach)
Most social traffic proved low-quality for conversions
Google’s social signals experiment failed (Google+ shutdown)
Social became a marketing channel, not a search replacement
The term “SMO” died; nobody uses it today

Content Marketing Institute’s retrospective analyzed the SMO boom as “consultants creating demand for solutions to non-problems.”

The GEO Parallel Is Uncomfortable

Like SMO in 2011, GEO in 2026:

Positions itself as revolutionary
Claims traditional approaches are obsolete
Attracts new consultants without deep expertise
Lacks clear differentiation from existing disciplines
Faces measurement challenges
Has passionate proponents and skeptical veterans
May represent a real shift, or a consulting gold rush, or both

FAQ

Q: Is GEO a real discipline or just rebranded SEO?

Q: Should I block AI crawlers or allow them?

It depends on your business model and whether you’re receiving value. According to Originality.AI’s research, you should block AI crawlers if:

Your traffic from AI search is <5% of total after 6 months
You’re a subscription/paywalled publisher
You’ve received no attribution despite being cited
Your revenue model requires page views/ads

Allow AI crawlers if:

You’re e-commerce (AI search users convert well)
You’re building brand awareness over direct traffic
You’ve negotiated licensing deals (like Reddit with Google)
You’re testing and measuring impact

Use robots.txt to block specific crawlers: GPTBot (OpenAI), Google-Extended (Google AI), CCBot (Common Crawl), anthropic-ai, and PerplexityBot.

Q: How do I measure GEO success?

This is the hardest question because attribution is murky. BrightEdge recommends:

Citation tracking: Use tools like Brand24, Mention, or Berify to monitor when your brand/content is cited in AI responses, even without links.

AI traffic segmentation: Create separate GA4 traffic sources for known AI referrers (chatgpt.com, perplexity.ai) and crawlers.

Query sampling: Manually test 50-100 relevant queries monthly across platforms, documenting citation rates.

Brand search trends: If AI exposure is working, you should see increased branded searches in Google (the “billboard effect”).

According to Ahrefs’ measurement guide, meaningful AI search impact shows:

15%+ of citations result in brand search increases
AI traffic converts at >50% the rate of organic search
Citation volume grows >10% month-over-month

Q: Will AI search kill traditional SEO?

Almost certainly not. According to Gartner’s 2026 technology predictions, even in optimistic AI adoption scenarios, traditional search will represent 65-75% of search volume through 2030. Why?

Commercial intent queries (buying, booking, comparing) work better with traditional results
Local queries need maps and specific location data
Complex research requires exploring multiple sources
Niche topics aren’t worth AI systems’ computation costs
Google’s monopoly and ad revenue create massive resistance to change

Q: Is the AI search hype comparable to voice search hype?

Partially, but AI search has stronger fundamentals. According to Pew Research’s technology adoption comparison:

Voice search adoption peaked at 27% of internet users (2018) and declined to 19% (2025) because:

Accuracy issues persisted
Social awkwardness of speaking queries publicly
No compelling advantage over typing for most queries
Privacy concerns

AI search adoption is currently 18% and growing because:

Provides genuinely better answers for synthesis queries
Text-based (no social awkwardness)
Improving rapidly
Backed by major platforms (Google, Microsoft, OpenAI)

Q: What’s the biggest risk of ignoring GEO?

For most businesses: almost none in 2026. According to Forrester’s risk assessment, only 7% of businesses face material risk from not optimizing for AI search currently.

You face risk if:

Your competitors are gaining AI search visibility while you’re invisible
Your audience is early adopters (tech, crypto, AI industries)
You’re in e-commerce or local services where AI recommendations drive decisions
You’re B2C with high competition and fungible products

You face minimal risk if:

Your audience is 40+ (lower AI search adoption)
You’re B2B with complex sales cycles
You have strong brand equity
Your traffic is primarily direct/branded search

Q: What skills differentiate GEO from traditional SEO?

According to LinkedIn Learning’s skills analysis, GEO-specific skills include:

Technical:

Understanding RAG (Retrieval-Augmented Generation) architectures
Prompt engineering to understand AI search behavior
API usage to query AI platforms programmatically
Python for automated citation monitoring

Strategic:

Multi-platform optimization thinking (no unified algorithm)
Passage-level vs. page-level optimization
Citation economics vs. traffic economics
Content extractability assessment

Measurement:

Attribution modeling without standard analytics
Brand impact measurement
Citation-to-traffic correlation analysis
Cross-platform visibility tracking

Q: Should agencies create separate GEO service offerings?

But Backlinko’s agency analysis warns against making GEO a completely separate offering because:

The tactics overlap 70-80% with SEO
Measurement is immature
ROI is unproven for most verticals
Platform fragmentation makes it complex to deliver

Better approach:

Integrate AI search considerations into SEO/content services
Use “GEO” in positioning and marketing
Price based on value (visibility across all search surfaces)
Set realistic expectations about measurement
Focus on fundamentals that work across systems

The Verdict

The SEO vs. GEO debate isn’t fundamentally about optimization tactics or acronyms. It’s about anxiety.

The anxiety of relevance: SEO practitioners worrying their discipline is being disrupted and their expertise devalued.

The anxiety of opportunity: New entrants worried they’ll miss the ground floor of the next big thing.

The anxiety of clients: Marketing leaders worried their competitors have figured out something they haven’t.

The anxiety of business models: Publishers watching their traffic and revenue evaporate with no clear alternative.

Psychology Today’s analysis of technology adoption anxiety notes that industries facing disruption consistently exhibit:

Taxonomic debates (what to call the new thing)
Camp formation (traditionalists vs. revolutionaries)
Gold rush dynamics (consultants rushing in)
Credibility warfare (dismissing opponents’ expertise)
Premature standardization attempts

We’re seeing all of these in the GEO debate.

What we know for certain:

User behavior is changing, slowly
Different systems retrieve and present information differently
Many “GEO tactics” are rebranded fundamentals, but weighting differs
Measurement is immature and attribution is hard
ROI is unproven for most business models
The hype exceeds the reality, but the reality is still meaningful

As Avinash Kaushik wisely noted, “In digital marketing, the taxonomy debates are inversely correlated with actionable insights.”

What’s your take? Are you optimizing for AI search, blocking AI crawlers, or waiting for clearer ROI data? The honest answer is that nobody knows the “right” strategy yet—and that’s uncomfortable, but it’s the truth.

AI Overviews