Marketing, Ads, and AI Visibility: What Actually Moves the Needle

VZ Lens

From the VZ perspective, this topic matters only when translated into execution architecture. Paid reach can create attention bursts, but durable AI visibility comes from structured authority and citation-worthy content architecture. The real leverage is in explicit sequencing, ownership, and measurable iteration.

[!abstract] Summary This research paper explores how AI-powered search is transforming the entire digital marketing and advertising ecosystem. We examine the future of Google Ads, the transformation of PPC (pay-per-click), GEO (Generative Engine Optimization) techniques, and the specific steps a brand can take to appear in the responses of ChatGPT, Perplexity, Claude, and Gemini.

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The Sounds of Coworking and Invisible Change

I’m sitting on the windowsill of a coworking space in Vienna, warmed by the afternoon sun. In the background, I hear a rhythmic but irritating tapping of a keyboard, then suddenly silence. From another corner, the clink of a coffee cup, then once again, only the hum of the air conditioner. This alternation of noise and silence feels strangely familiar. It’s like my attention on the screen: one moment immersed in the details of an ad campaign, the next clinging to a completely different, seemingly random thought.

I look around. Everyone is preoccupied with something invisible. Graphs on one screen, an endless chat window on another. The question that sometimes silences even the keyboard is one that perhaps concerns us all: how can one become visible in a space we cannot see? Where answers are not lists, but conversations? Where search is not a gateway, but a continuous, buzzing dialogue?

1. The Marketing Earthquake — What’s Happening Right Now?

1.1 The Search Revolution in Numbers

The fundamentals of digital marketing underwent a radical transformation between 2024 and 2026. Some staggering data:

Metric	Value	Source
Percentage of zero-click searches (no clicks)	69% of all searches	Click-Vision, 2026
Zero-click rate on mobile	77%	Click-Vision, 2026
CTR decline for AI Overviews	-61% (from 1.76% to 0.61%)	Dataslayer, 2026
Expected decline in traditional search traffic by 2026	-25%	Gartner forecast
Expected decline by 2028	-50%	AthenaHQ analysis
ChatGPT weekly active users	900 million	DemandSage, 2026
ChatGPT daily prompt processing	2.5 billion	DemandSage, 2026
Google AI Overviews monthly users	1.5 billion	ALM Corp, Q1 2025

[!warning] What does this mean in practice? In seven out of every ten searches, the user doesn’t even open a single webpage. AI summarizes the answer, the user gets what they wanted, and moves on. This is the “zero-click revolution”—and it’s not a vision of the future, but the present.

1.2 The Collapse of the Old World

Traditional digital marketing rested on three pillars:

1. SEO (search engine optimization) — write good content, get on the first page
2. PPC (pay-per-click) — pay for clicks on Google Ads
3. Content marketing — attract visitors with valuable content

All three pillars are crumbling:

• SEO: When AI answers the question above the search results, the “10 blue links” (traditional results list) receive fewer and fewer clicks. According to some metrics, the CTR of the top organic result dropped by 79% when the AI Overview appeared above it.
• PPC: Ads are pushed below the AI summaries, and fewer people scroll down to see them. A 60% zero-click rate means that half of users don’t even see the ads.
• Content marketing: If your content appears in the AI’s response (quoted, not linked), traffic won’t reach your website. The brand gets a mention, but the click doesn’t happen.

1.3 The New Players

Five major players are shaping the new order in the AI search market:

Platform	Monthly Users	Advertising Model	Unique Features
Google AI Overviews	1.5 billion	Ads are integrated	Dominates 90%+ of the search market
ChatGPT	900M weekly active users	No ads (for now)	Largest LLM user base
Perplexity	100M+ users	Discontinued ads (Feb. 2026)	Returned to subscription model
Google Gemini	Market share: 14.7%→25.2%	Google ecosystem	Strong growth
Claude	Growing	No ads	Research quality

[!tip] The lesson from Perplexity Perplexity began experimenting with ads in November 2024—in the form of “sponsored follow-up questions.” In February 2026, it completely withdrew the advertising program. The reason: erosion of user trust. “The user must believe that this is the best possible answer,” a Perplexity executive told the Financial Times. This decision shows that AI search and the traditional advertising model may be fundamentally incompatible.

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2. The Google Ads Empire — Growth and Threat at the Same Time

2.1 The Paradox of the Numbers

Google’s advertising revenue continues to grow — but there is increasing tension behind this growth.

Period	Advertising Revenue	Growth
Q4 2025	$82.3 billion	+13.5% YoY
Q4 2025 — Search & Ads	$63.07 billion	+17%
Full Year 2025	$400+ billion	First time
Estimated Annual 2026	$300+ billion (advertising only)	Analyst estimate

How is it possible for revenue to grow while clicks are declining?

1. CPC inflation — The cost per click is rising because advertisers are competing for fewer clicks
2. Performance Max — AI-powered campaigns convert more effectively
3. New formats — Ads integrated into AI Overviews (In 2025, the share of AI Overviews with ads increased from 5% to 25% over eight months — a 394% increase)
4. Global SMB expansion — Influx of small and medium-sized businesses

2.2 Performance Max — The New King of AI Campaigns

Performance Max (PMax) is Google’s fully automated, AI-driven campaign type that runs simultaneously across Search, YouTube, Display, Gmail, Discover, and Maps.

Status in 2026:

• PMax campaigns account for 45% of all Google Ads conversions
• 35% more conversions and 20% lower CPA (cost per acquisition) compared to manual campaigns
• For the average enterprise account, PMax manages 80% of total ad spend (up from 55% in 2024)

[!note] PMax — The Other Side of the Coin Performance Max is effective, but advertisers have less and less insight into exactly where, when, and to whom their ads are shown. Google’s AI decides on the tactical elements; advertisers must focus on the strategic level: goals, KPIs (key performance indicators), and creative assets.

2.3 The AdSense Crisis — A Publisher’s Nightmare

In January 2026, Google’s advertising infrastructure suffered catastrophic failures: publisher revenues plummeted by 50–90% overnight (January 13–15). Although this was partly a technical issue, the trend is clear: AI Overviews structurally undermine the AdSense model because fewer users are reaching publisher sites.

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3. GEO — Generative Engine Optimization

3.1 What is GEO?

GEO (Generative Engine Optimization) is the field of study concerned with how to get a brand, product, or piece of content included in AI-generated responses. It relates to traditional SEO like an electric car relates to an internal combustion engine: the principles are similar, but the mechanism is completely different.

Traditional SEO: GEO:
Keyword → Ranking → Link → Click     Entity → Relevance → Mention → Trust
 ↓
 There may be NO click, but the brand
 appears in the AI’s response

3.2 The Five Pillars of GEO

According to Search Engine Land and other sources, five key factors determine visibility in AI:

1. Content Retrievability

AI systems must be able to find your content. If your website is inaccessible to crawlers for technical reasons, you won’t appear in search results.

Actions to Take:

• Optimize robots.txt and sitemap
• Fast page loading
• Clean URL structure
• Content must be publicly accessible (not behind a paywall)

2. Content Alignment

AI systems highlight content that clearly and unambiguously answers the question. It’s not keyword density that matters, but contextual relevance.

What to do:

• Write as if you were answering a question
• Use definitions, comparisons, and “why it matters” type paragraphs
• Structured content: tables, lists, summaries

3. Competitive Differentiation

If ten websites write about the same topic, AI will favor the one that offers a unique perspective. Original research, proprietary data, and unique opinions are more valuable than summaries.

Things to do:

• Publish original research findings
• Provide unique data and statistics
• State your own position

4. Authority Signals (Authority Signals)

AI systems monitor how reliable a source is. This is the concept of E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness).

Actions:

• Create author pages with a genuine professional background
• Links and backlinks from authoritative sites
• Appearances in industry media, podcasts, and conferences
• Build a Google Knowledge Panel

5. Entity Mapping

AI systems think in terms of entities (uniquely identifiable things: people, brands, products, concepts), not keywords. If your brand becomes an “entity” in the eyes of AI, it is much more likely to appear in search results.

Actions:

• Implement Schema.org markup (structured data)
• Consistent brand name usage across all platforms
• Presence on Wikipedia and Wikidata
• Linking to related entities (e.g., industry, technology, region)

3.3 The Role of Structured Data (Schema Markup)

Schema markup is one of GEO’s most important technical tools. Schema.org—which was jointly created by Google, Bing, Yahoo!, and Yandex in 2011—now supports 811 content types.

[!important] Why is it critical? An Evertune study showed that pages with structured data appear in AI-generated summaries 58% more often than those without. Schema markup “removes ambiguity”—the AI system doesn’t have to guess what the content means.

Priority schema types:

Schema type	What it’s for	Who uses it
Organization	Company information, contact details	All businesses
Product	Product details, price, availability	E-commerce
Article	Articles, author information	Publishers, blogs
FAQPage	Q&A pairs	Service providers
HowTo	Step-by-step guides	Tutorial sites
Person	Personal expert profile	Thought leaders
LocalBusiness	Local business data	Local businesses

3.4 The Strengthening of E-E-A-T in the Age of AI

E-E-A-T (Experience, Expertise, Authority, Trustworthiness) is a Google quality guideline, but AI search systems rely on it even more heavily than traditional search.

According to a study:

• A 38% increase in media appearances and influencer opportunities for brands with strong E-E-A-T
• A 67% higher chance that potential customers will contact them directly
• This “citation premium” shows that AI search engine optimization pays off with compound interest

The difference with Entity SEO (entity-based search engine optimization):

Traditional SEO optimizes for keywords. Entity SEO focuses on entities—that is, things that AI systems can clearly identify. For example, “Nike” is not a keyword but an entity to which AI automatically associates concepts such as “running shoes,” “sports brand,” “Just Do It,” and many others.

According to Neil Patel’s analysis, Entity SEO “prioritizes mentions and human conversation over keywords.”

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4. How to Get Into AI Answers — Specific Techniques

4.1 LLMO — Large Language Model Optimization

LLMO (Large Language Model Optimization) is the practice by which a brand can increase its chances of appearing in the responses of LLMs (ChatGPT, Claude, Gemini, etc.).

LLMs decide which brands to recommend based on three main factors:

1. Frequency in training data — The more often your brand appears in the LLM’s training data (websites, books, Reddit conversations, news), the more likely it is to be mentioned
2. Contextual relevance — The LLM recommends what it deems most appropriate for the question
3. Signs of authority — References, quotes, expert opinions

[!warning] SparkToro Research Warning SparkToro’s 2026 research showed that LLMs are extremely inconsistent in their brand recommendations. Asking the same question to ChatGPT, Claude, and Perplexity can yield different brands. This means that measuring and optimizing AI visibility is much more complicated than tracking traditional SEO rankings. [UNVALIDATED: the exact inconsistency rate is unknown]

4.2 The 12 Proven LLMO Tactics

Based on Search Engine Land, Neil Patel, and other sources:

#	Tactic	Impact	Difficulty
1	Statistics and citations in content	+30-40% AI visibility	Medium
2	Structured data (Schema markup)	+58% citation chance	Technical
3	Building an author profile (E-E-A-T)	Long-term authority	Low
4	Wikipedia/Wikidata presence	Entity recognition	Difficult
5	Reddit, Quora presence	LLM training data	Medium
6	Advertorials (sponsored content) on reputable publishers	Indirect AI exposure	Expensive
7	FAQ sections in clear Q&A format	AI-friendly structure	Low
8	Comparative content (vs. articles)	Recommendation context	Moderate
9	Podcast and video appearances	Cross-platform mentions	Moderate
10	Digital PR (press coverage)	Authority signals	Expensive
11	Consistent brand name across all platforms	Entity coherence	Low
12	Publication of original research	Unique source value	Difficult

4.3 Case Studies — Real Results

Several documented case studies prove that GEO/LLMO optimization delivers measurable results:

Case	Intervention	Result
Industrial manufacturer	GEO optimization	+2300% AI traffic
Amico Lighting (LED)	GEO program, 12 weeks	80%+ AI mention rate (previously 0%)
Automotive websites	Content + Schema	+200% AI referral traffic
Anonymous B2B company	Structure-focused approach	+540% Google AI Overview mentions
B2B Webflow agency	“Clarity-focused” rewrite, 6 weeks	32% of SQLs from AI search engines (ChatGPT, Perplexity)

[!tip] The Tesla Effect A study showed that Tesla is a “cyborg brand”—that is, a brand recommended by LLMs at an exceptionally high rate. The reason: Tesla’s communication is function- and feature-focused (battery life, software, tech stack) and does not use aspirational marketing. LLMs prefer objective, factual content over marketing copy. In contrast, the Lincoln car brand—which tends to use “dream marketing”—appears much less frequently in AI recommendations.

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5. The Future of PPC — It Won’t Die, But It Will Transform

5.1 PPC Isn’t Going Away

Despite alarming statistics, PPC (pay-per-click advertising) isn’t dying:

• 98% of PPC professionals continue to use Google Ads as their primary platform
• 80% of businesses continue to rely on PPC for growth
• Google’s ad revenue continues to grow

5.2 What Is Changing

1. CPC inflation: Cost-per-click rates are rising across all platforms because advertisers are competing for fewer clicks
2. Loss of transparency: AI-powered campaigns (Performance Max) provide advertisers with less data
3. New ad formats: Ads integrated into AI Overviews and AI Mode
4. Creative automation: By the end of 2026, campaigns will automatically generate creative variations based on performance data

5.3 Google AI Max — The New Advertising Paradigm

In 2026, Google introduced AI Max for Search campaigns—the next step after Performance Max. AI Max:

• Automatically expands keyword targeting based on AI interpretation
• Dynamically allocates budget across channels
• Uses real-time predictive conversion modeling

[!caution] The Erosion of Advertiser Control According to a February 2026 analysis by GROAS.AI, Google Ads AI is “quietly eroding advertiser control in ways that serve Google’s revenue goals, not advertisers’ interests.” This is one of the biggest points of tension in the PPC industry.

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6. Measurement and Monitoring — How to Measure AI Visibility?

6.1 The New Metrics

Traditional SEO/PPC metrics (organic ranking, CTR, CPC) are insufficient in the age of AI. New metrics are needed:

Metric	Description	Why It Matters
AI Mention Rate	How often AI mentions your brand	Basic visibility indicator
Citation Share of Voice	The proportion of AI citations compared to competitors	Market position
Prompt Coverage	How many relevant prompts (questions) the brand appears in	Coverage
Recommendation Share	The proportion of recommendations among competitors	Competitive Position
LLM Consistency	How consistently the brand appears across different LLMs	Stability
Contextual Sentiment	In what context does the AI mention the brand (positive/negative)	Sentiment

6.2 AI Visibility Tools — 2026 Comparison

The AI visibility monitoring market is growing explosively. More than 24 platforms offer GEO/AI visibility services.

Tool	Focus	Price/month	Strength
SE Ranking (AI Visible)	Full GEO + SEO integration	Varies	AI visibility embedded in the SEO stack
Otterly.ai	Google AI Overview monitoring	$29–489	Google-focused, easy to use
AthenaHQ	Prompt tracking + automated content	$295+	End-to-end content pipeline
Evertune	Enterprise LLM monitoring	$3000+	1M+ prompts/month, statistical depth
Peec AI	GEO platform	Varies	Competitive analysis
Profound	AI search analytics	Varies	In-depth analysis
Semrush AI Toolkit	AI visibility add-on	Existing subscription	Familiar interface
BrightEdge	Enterprise AI monitoring	Enterprise	Structured data audit
Scrunch	AEO/GEO platform	Variable	Easy to use
Adobe LLM Optimizer	Enterprise GEO	Enterprise	Adobe ecosystem

[!tip] Which one should you choose?

• Small and medium-sized businesses, Google-focused: Otterly.ai ($29/month) — simple, targeted
• Marketing agency: SE Ranking AI Visible — SEO + GEO in one place
• Large enterprise, multiple LLMs: Evertune ($3000+/month) — statistical depth
• Content-heavy strategy: AthenaHQ ($295/month) — automatic content generation
• First steps (free): Manual prompt testing on ChatGPT, Claude, Perplexity, and Gemini

6.3 How to Test Manually?

Before spending money on tools, perform a free AI visibility audit:

1. Open 4 platforms: ChatGPT, Claude, Perplexity, Google Gemini
2. Ask the same questions your customers would ask (e.g., “What’s the best [product/service] in the [category]?”)
3. Take notes:
   • Does your brand appear?
   • In what context is it mentioned?
   • Which competitors are mentioned instead of you?
   • Are there any inaccuracies?
4. Repeat weekly — monitor trends

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7. Preparation Strategy — Specific Steps

7.1 List of Immediate Actions (0–30 days)

Step	What to Do	Why
1	AI visibility audit — test your brand on 4 AI platforms	To establish a baseline
2	Implement Schema markup (Organization, Product, FAQ)	Foundation for an AI-friendly structure
3	Create author pages with authentic professional credentials	Strengthen E-E-A-T
4	Add FAQ sections to key pages	Q&A format for AI
5	Checking Google Business Profile and knowledge panel	Entity recognition

7.2 Mid-Term Strategy (1–3 months)

Step	What to do	Why
6	Content rewriting — adding statistics, quotes, and source references	+30-40% AI visibility
7	Creating comparative content (e.g., “X vs. Y: Which is better?”)	LLM recommendation context
8	Establishing a presence on Reddit and Quora in category-relevant subreddits	LLM training data source
9	Digital PR campaign — appearances in industry media	Strengthening authority signals
10	Implement an AI monitoring tool (Otterly or SE Ranking)	Continuous measurement

7.3 Long-Term Development (3–12 months)

Step	What to do	Why
11	Publish original research in the field	Unique source value for AI
12	Build a Wikipedia/Wikidata presence	Foundation for entity recognition
13	Podcast and video presence (YouTube, Spotify)	Cross-platform mentions
14	Building topical authority — in-depth coverage of a topic	AI seeks the “best source”
15	Revamping the PPC strategy — Performance Max + AI Mode ads	The new advertising paradigm

7.4 The Transformation of Content Strategy

In the age of AI, content creation follows different rules:

OLD RULES: NEW RULES:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Keyword density optimization  →  Entity clarity and context
Long content = good →  Structured, AI-processable = good
Backlink building →  Brand mentions + Digital PR
Meta description optimization  →  Schema markup + structured data
Keyword research →  Prompt research (what are people asking AI?)
Measuring organic rankings →  AI mention rate + citation share
Click-through rate →  Brand impression in the AI response

[!abstract] Format-First Thinking In 2026, the focus must shift toward “format-first thinking.” Users don’t just want an answer—they want it in the format that best fits the question. This could be a table, a comparison, a step-by-step guide, or a short definition. AI systems favor content that offers the same information in multiple formats.

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8. The Future of AI Advertising — What Comes After 2026?

8.1 Three Possible Scenarios

Scenario A — “Google Dominance” (probability: 50%)

Google successfully integrates ads into AI Overviews and AI Mode. Ad revenue continues to grow; PPC transforms but does not disappear. Other AI platforms (ChatGPT, Claude) do not introduce ads.

Impact: Marketing spending shifts toward Google’s AI platforms. Traditional keyword advertising takes a back seat, while “brand experience” ads dominate.

Scenario B — “Fragmentation” (probability: 35%)

The AI search market fragments. Every platform develops its own advertising model. ChatGPT introduces some form of sponsored content (not traditional advertising). Brands must be present on 4–5 platforms.

Impact: Marketing costs rise (more platforms = more optimization). AI visibility monitoring tools experience explosive growth.

Scenario C — “Subscription-based world” (probability: 15%)

The Perplexity model will prevail: AI search engines will remain ad-free, with subscription fees covering costs. Advertising will be relegated to traditional display and social media platforms.

Impact: The importance of GEO/LLMO increases (paid visibility is not an option); organic AI visibility becomes the only way to gain visibility.

8.2 The Artificial Intelligence Advertising Paradox

There is a fundamental tension between AI search and advertising:

• The value of AI search engines lies in their ability to provide objective, best-in-class answers
• By its very nature, advertising skews answers in favor of the paying party
• If AI answers are distorted by ads, users lose trust (see: Perplexity’s withdrawal)
• Without ads, AI platforms must find other revenue sources

This paradox will determine the direction of development in the coming years. [UNVALIDATED: the emergence of long-term market equilibrium is uncertain]

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9. Summary and Key Findings

Key Takeaways

1. The zero-click revolution is here — 69% of searches don’t generate a click, and this number is growing
2. GEO is not optional — if you don’t optimize for AI search engines, you’ll become invisible
3. PPC isn’t dying, but it is evolving — Performance Max and AI Mode ads are replacing manual campaigns
4. Entity building is key — AI systems think in terms of entities, not keywords
5. Structure is more important than length — AI favors well-structured content with Schema markup
6. Measurement is more complex — new metrics (AI Mention Rate, Citation Share of Voice) and new tools are needed
7. The Perplexity precedent — there is a fundamental tension between AI search and traditional advertising
8. E-E-A-T has been reinforced — experience, expertise, authority, and trustworthiness are more important than ever
9. You need to be present on multiple platforms — ChatGPT, Gemini, Perplexity, and Claude are all separate channels
10. Early adopters have an advantage — AI visibility optimization delivers measurable results in 4–12 weeks

Priority Matrix

 HIGH IMPACT
                        │
    ┌───────────────────┼───────────────────┐
    │ │ │
    │  Schema markup    │  Original research  │
    │  E-E-A-T building   │  Wikipedia presence. │
    │  FAQ sections     │  Digital PR │
    │ │ │
LOW ───────────────┼──────────────── HIGH
EFFORT │ EFFORT
    │ │ │
    │  Consistent     │  Podcast/video    │
    │  brand name │  Reddit/Quora     │
    │  AI audit │  AI monitoring    │
    │ │  tool │
    └───────────────────┼───────────────────┘
 │
 LOW IMPACT

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10. Resources and References

• Search Engine Land — GEO, LLMO, PPC trends (searchengineland.com)
• HubSpot — AI search visibility playbook (blog.hubspot.com)
• Conductor — Brand mentions in AI (conductor.com)
• Microsoft Advertising Blog — AI search guide (about.ads.microsoft.com)
• Forbes Communications Council — GEO birth (forbes.com)
• Evertune — AI visibility tools (evertune.ai)
• AthenaHQ — GEO platforms (athenahq.ai)
• Neil Patel — LLMO, Entity SEO (neilpatel.com)
• Backlinko — Entity SEO, AI optimization (backlinko.com)
• SparkToro — LLM recommendation inconsistency research (sparktoro.com)
• ALM Corp — Google Ads revenue, Perplexity analysis (almcorp.com)
• DemandSage — ChatGPT statistics (demandsage.com)
• Gartner — Search traffic decline forecast
• Otterly.ai — AI search monitoring (otterly.ai)
• SE Ranking — AI Visible platform (seranking.com)
• GROAS.AI — Google Ads AI state 2026 (groas.ai)
• Dataslayer — CTR impact analysis (dataslayer.ai)
• Click-Vision — Zero-click statistics (click-vision.com)
• First Page Sage — AI chatbot market share (firstpagesage.com)
• Harvard Business Review — LLMs overtaking search (hbr.org)
• TechBusinessNews — AdSense crisis 2026 (techbusinessnews.com.au)
• Campaign US/Asia — Perplexity ad abandonment (campaignlive.com)

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[!quote] Closing thoughts “The user must believe that this is the best possible answer in order to continue using the product and be willing to pay for it.” — Head of Perplexity, Financial Times, February 2026

This single sentence sums up the fundamental tension between AI search and marketing—and this tension will define advertising and marketing strategies in the coming years.

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Research date: 2026-03-09 | LLMOFUTURE project | Created by: Claude Code (cc-research pipeline) Data and statistics are sourced from the referenced sources. Forecasts and scenarios are based on available data; future developments may differ.

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