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Helping Global Heads of Marketing, CMOs, and Enterprise Leaders understand and adapt to the emerging AI-powered search ecosystem.

The Evolution of SEO: How AI Search is Rewriting the Rules of Visibility

By Sophie Carr, Strategic Advisor in GAIO Marketing & AI Visibility

A symbolic fusion of AI search and human strategy: two mirrored faces made of living forest. This visual metaphor shows how AI search visibility grows from content rooted in strategic insight nourished by real expertise, designed to answer real questions. For those who can't see the image: Imagine AI search as a forest of knowledge, where human minds plant the seeds that help brands show up.

Table of Contents


1. Why AI Search Matters Now

AI-native search isn’t just a technical innovation. It’s one of the biggest untapped visibility opportunities most CMOs are missing today. And not because they aren’t smart. Because the rules changed faster than the playbook did.

Platforms like ChatGPT, Gemini and Perplexity are already influencing how people discover, compare, and evaluate brands. The visibility they offer isn’t random. it’s earned. But most teams aren’t building content that earns it.

According to Gartner, by 2026, search engine volume will drop 25% due to AI chatbots and other virtual agents. That shift has already started. The brands that move early will gain a compounding advantage. Those who wait may not realise they’ve been left out until the traffic is already gone.

2. What Changed in Search Behaviour

Buyers are no longer searching with keywords. They’re asking full questions. And they expect real answers.

AI isn’t delivering a list of ten blue links. It’s responding with a summary, a synthesis, sometimes even a recommendation. That response is drawn from what the model has been trained on and that doesn’t automatically include your blog, your landing page, or your product page.

That’s why showing up isn’t something you can assume. It’s something you need to engineer.

3. Where Traditional SEO Falls Short

Traditional SEO has value. But it wasn’t designed for AI. We’ve relied on backlinks, keyword clusters, and SERP tricks. That strategy isn’t dead it’s just no longer the only one.

Search is now answer-led. If your content isn’t designed to be parsed, trusted, and reused by AI, then it’s probably ignored. That’s not a small problem it’s an existential one for your visibility.

4. What AI Search Engines Actually Use to Surface Content

Let me be plain: AI platforms don’t reward noise. They reward clarity, structure, and consistency.

They tend to favour:

  • Clean, answer-first formatting

  • Structured content that’s easy to understand

  • Consistent brand presence across credible sources

  • Semantic alignment to topics

  • Verified authorship

And they punish fluff. According to research from the University of Surrey, AI-generated content is increasingly flooding the web with low-quality, unreliable material. That means the bar for relevance is rising. Your content needs to add value in a meaningful way.

This is why human intelligence must remain the manager. AI can assist. But someone needs to be accountable for quality, for truth, and for how trust is earned.

5. The GAIO Shift: Strategy Over Tactics

Generative AI Optimisation isn’t just a new acronym. It’s a new operating system for marketing.

GAIO means building with intention. It means asking: what would a real person ask about this topic? And would our brand be a helpful answer?

This is not about hacking visibility. It’s about earning presence in systems that are increasingly acting as filters between you and your next customer.

It’s also a choice. You can either leave it to chance or take control.

6. How CMOs Are Responding

In private, many leaders are saying the same thing: “We know AI is shifting the landscape. But we haven’t figured out how to lead on it.”

They’re right to pause. But not for too long.

This is not a time to wait for the ‘perfect’ tool - which we are working on. It’s a time to put human strategy in the driver’s seat and let AI be the co-pilot.

7. The First Step to Showing Up

You don’t need to overhaul everything. But you do need to start:

  • Ask: what are three questions our audience would ask AI that we should be the answer to?

  • Check if your brand is mentioned when those questions are asked.

  • Structure a clear, helpful, trustworthy page that answers them.

  • Use schema. Use authorship. Use your judgment.

And do it now. Not when it’s convenient. When it’s necessary.

8. FAQ

Q: Is SEO dead?

No. It’s evolving. And GAIO is the logical next step.

Q: Can we use tools to track this?

Yes. There are ways to audit AI visibility manually or through Share of Voice trackers.

Q: Should we be updating all our content?

No. Start with high-intent pages and strategic knowledge hubs.

Q: How long does this take?

Brands have appeared in AI results within weeks. But sustainable visibility requires iteration and oversight.

I’ve been building toward this moment for years, even before we had a name for it. And I believe the future belongs to brands that optimise for trust.

If you're looking for support with your AI marketing strategy, then book a free consultation at https://calendar.app.google/EFjvPpX6XXZ3i3sx5.

– Sophie

What is the right term for ranking in AI search? GAIO vs AIO vs AEO vs SEO vs GEO (let’s clear it up)

By Sophie Carr, GAIO Marketing

A surreal depiction of AI-generated knowledge trees forming a digital forest, symbolizing the growth and evolution of artificial intelligence in search and discovery. This AI art was created by Sophie Carr, founder of GAIO Marketing.

Table of Contents

If SEO helps you rank in Google, what helps you rank in ChatGPT?

That's the question I get asked the most by marketing leaders right now, especially those already confident with SEO.

And I get it. The jargon around AI marketing is confusing. Some people say it's GEO (Generative Engine Optimisation). Others say it's AIO or AEO. I say: it's time we simplified the terminology and got aligned.

So, in this blog, I’m going to answer your questions.

  1. What is GAIO?

GAIO stands for Generative AI Optimisation. It’s about making your content more visible in generative AI tools like:

These platforms don’t work like Google Search. They don’t show 10 blue links. Instead, they summarise, remix, and rewrite the internet to generate responses to user queries.

So if your content isn’t optimised for the way LLMs (large language models) read, understand, and cite information, then it gets left out.

GAIO ensures your content is:

  • Structured clearly

  • Backed by reliable sources

  • Easy for AI models to parse (understand)

  • Factually accurate and coherent

Want to go deeper into the GAIO Strategy? I break it down here: How to Rank in AI: The GAIO Strategy

  1. Why is GAIO so important right now?

Because AI is already changing how people discover brands.

A new Adobe Analytics report (2025) revealed that traffic to U.S. retail websites from generative AI sources jumped 1,200% in the last year alone.

Let that sink in.

We’re witnessing a massive shift in how consumers find and interact with content. AI tools are no longer just novelty chatbots; they’re full-blown discovery engines.

That means:

  • Buyers are asking ChatGPT what to buy.

  • Parents are asking Gemini what snacks to pack.

  • CMOs are asking Claude how to plan their 2025 GTM strategy.

If you’re not optimising your content for AI, you’re missing out on a rapidly growing channel. And worse: you’re letting someone else get cited as the authority in your space.

  1. Wait, isn’t GAIO just SEO?

Not exactly.

SEO = Optimising for search engines. Think keywords, backlinks, load speed, and mobile usability. It works to help you rank in traditional engines like Google and Bing.

GAIO = Optimising for LLMs. Think clarity, citations, entity-based structure, AI-trainable formatting, and question-led content.

They work together - but they target different algorithms.

  1. What is AEO?

AEO stands for Answer Engine Optimisation. It’s a bridge between SEO and GAIO.

Answer engines (like Google’s Featured Snippets, Knowledge Panels, and even Alexa or Siri) aim to give answers instead of showing links.

AEO ensures your content shows up as:

  • Featured snippets

  • FAQs

  • Rich cards

  • Voice assistant results

So think of it this way:

  • SEO = Gets you into the top of search results

  • AEO = Gets you directly quoted by answer-based engines

  • GAIO = Gets you summarised, cited, and included in AI-generated responses

All three are valuable, but they are not interchangeable.

  1. What are all these AI terms people throw around?

To fully understand GAIO, we need to understand the history of artificial inteligence.

AI Terminology Explained: This AI knowledge graphic by GAIO Marketing visually breaks down the evolution of artificial intelligence, starting from Artificial Intelligence (AI) to Machine Learning (ML), Neural Networks (NN), and Deep Learning (DL). It highlights key AI advancements like Transformers, Generative AI (GenAI), Generative Pre-trained Transformers (GPT), and Large Language Models (LLMs), leading to GPT-4.5 and ChatGPT. Understanding these terms is crucial for AI search optimization, GAIO (Generative AI Optimization), and ranking in AI-powered search. Learn more at www.gaio-marketing.com and stay ahead in AI-driven marketing, content creation, and SEO strategies.

The evolution of AI: How we got to ChatGPT and GAIO

AI has transformed from basic rule-based systems to powerful chat platforms that drive marketing, business, and education. Each stage of AI development solved a limitation from the previous one, leading to the technology we use today.

This guide breaks down the evolution of AI step by step.

  1. 1956 - AI starts (basic rules-based AI)

🤖 What happened? A group of brilliant minds, including John McCarthy, Marvin Minsky, and Claude Shannon, got together at the Dartmouth Conference to brainstorm a radical idea - machines that could think. AI was officially born!

❌ Limitation: Couldn’t learn or improve, only followed fixed rules.

🔜 Leads to: Machine Learning (ML), allowing AI to learn patterns from data instead of relying on rigid programming.

  1. 1980s - Machine learning (AI starts learning)

📊 What happened? Instead of just following rules, AI could now learn from data! This meant AI could spot patterns, like detecting fraud in banking or recognising handwritten numbers.

❌ Limitation: Still needed humans to manually select features (e.g., deciding what makes an email spam).

🔜 Leads to: Neural Networks (NN), automating feature selection and improving pattern recognition.

  1. 1990s - Neural Networks (AI Mimics the Brain)

🧠 What happened? Scientists like Geoffrey Hinton, Yann LeCun, and Yoshua Bengio brought Neural Networks back into the spotlight, helping AI recognise faces, speech, and objects - big wins for early Face ID and voice assistants.

❌ Limitation: Too shallow and early networks couldn’t handle complex real-world data.

🔜 Leads to: Deep Learning (DL), stacking multiple layers for more advanced learning.

  1. 2010s - Deep Learning (AI gets super smart)

🚗 What happened? Deep Learning revolutionised AI! Suddenly, AI could drive cars (Tesla Autopilot), translate languages (Google Translate), and even detect diseases from medical scans.

❌ Limitation: AI still forgot things easily and couldn’t handle long conversations.

🔜 Leads to: Transformers, a breakthrough that allowed AI to process entire sentences at once.

  1. 2017 - Transformers (AI understands language)

🔄 What happened? A team at Google, led by researchers Ashish Vaswani, Jakob Uszkoreit, and Noam Shazeer, developed the Transformer model. This was a game-changer (sorry for the buzzword but it's true)! AI could now process entire sentences all at once, rather than word by word.

❌ Limitation: AI could understand text but couldn’t generate natural human-like responses.

🔜 Leads to: Generative AI (GenAI), where AI could now create text, images, and videos.

  1. 2020 - Generative AI (AI starts creating)

✍️ What happened? AI got creative! It began writing blogs, generating images, and even composing music. OpenAI, led by Sam Altman, launched GPT-3, a massive AI model trained on 175 billion parameters. Other big players like Google DeepMind joined the race.

🖌 First Big Tools: Early advancements like GPT-3 gained attention mostly in tech circles but weren’t widely accessible. Tools like ChatGPT, Midjourney, and DALL·E didn’t reach the public until later, in 2022, when user-friendly interfaces became available.

❌ Limitation: Early models often produced inaccuracies (hallucinations) and couldn’t recall past conversations. Accessibility and security concerns also delayed broader adoption initially.

🔜 Leads to: Large Language Models (LLMs) and Generative Pre-trained Transformers (GPT), which enhanced text generation, creativity, and reliability.

  1. 2021 - Large Language Models (LLMs) make AI smarter

📚 What happened? GPT models like GPT-3 set new benchmarks for AI. They improved reasoning, handled complex queries, and maintained longer conversations. By 2021, advancements in these models were paving the way for broader applications.

❌ Limitation: Early models weren’t user-friendly and required technical expertise, making them inaccessible for most people.

🔜 Leads to: The launch of ChatGPT in 2022 provided an easy-to-use chatbot interface, making AI accessible to everyone and changing how people interact with technology.

  1. 2022-Present - ChatGPT (AI for Everyone)

💬 What Happened? OpenAI built on its GPT model, a powerful AI capable of generating human-like text, but it needed a platform where people could actually use it. That’s when ChatGPT was born, making AI accessible to everyone, even without technical expertise.

That’s when they created ChatGPT, the platform we all know and love today, making AI accessible to everyone, even without technical knowledge.

💡 Difference Between ChatGPT and GPT-4.5:

  • GPT-4.5 is the “brain” powering the responses - a Large Language Model (LLM) designed for advanced reasoning and text generation.

  • ChatGPT is the “mouth” - a simple and intuitive platform that lets anyone use GPT-4.5 for writing, research, marketing, and business tasks.

🚀 Breakthrough Moment: AI moved beyond research labs and became a mainstream tool for businesses, education, and content creation, powering everything from SEO and AI search visibility to customer support and content marketing.

  1. Why it’s called GAIO marketing (and not the other terms)

So, why GAIO Marketing? Why not AIO, GEO, or just SEO for AI?

Because the real shift happened with Generative AI (GenAI). That’s when AI stopped just analysing and started creating.

Before 2020, AI could recognise faces, detect spam, and even predict the next word in a sentence. But it couldn’t write an article, generate an image, or compose a song—until Generative AI came along.

And here’s the key: we’re not optimising for self-driving cars, facial recognition, or industrial robotics. Those are AI, but they’re not Generative AI. We care about optimising for AI that creates text. That’s why GAIO (Generative AI Optimisation) is about ranking in AI-generated responses, not just traditional search.

That’s what made tools like ChatGPT, Midjourney, and Google Gemini possible. And that’s exactly why it’s called Generative AI Optimisation (GAIO)—because we’re optimising for the AI that actually creates content, not just the AI that ranks websites like Google Search.

If AI is rewriting the internet, then GAIO is how you make sure your brand, business, or content gets included in that rewrite.

That’s the future of marketing. That’s GAIO.

  1. What are the benefits of optimising for LLMs — and can I afford to wait?

It’s a fair question: is this urgent, or can we treat GAIO like another marketing trend and put it on next year’s roadmap?

Here’s the reality:

Delaying GAIO could cost you visibility, leads, and authority.

The longer you wait, the more your competitors train the models to recognise their content, their language, and theirauthority. And once those models are trained, it takes significant effort (and often, time) to shift their preferences.

The benefits of acting now and ranking in AI search:

  • AI model familiarity: The sooner your content appears in AI outputs, the more likely it is to be reused.

  • Early mover advantage: LLMs reward clear, structured, consistent sources. The earlier you show up, the more weight you carry.

  • High-quality traffic: According to Adobe Analytics (2025), visitors arriving from AI-generated results spend 35% more time on site and convert 17% more often than those from traditional search. This isn’t just new traffic — it’s better traffic.

  • Reduced content waste: GAIO helps your existing content work harder, by preparing it for how AI assistants surface information.

Bottom line: Optimising for LLMs isn't just smart - it’s becoming essential.

The best time to start was yesterday. The second best time? Now.

  1. Final Thoughts on AI Search

If you’re trying to rank in AI, you can’t rely on old SEO tactics alone. You need to optimise your content for how AI thinks, not just how humans search.

That’s what GAIO is all about.

Let’s stop mixing up the terms and start using the right strategies. Because the future of content visibility? It’s being written by AI.

Sophie Carr, Founder of GAIO Marketing and an expert in ranking in AI search. She is standing in an office smiling at the camera with the forest outside.

  1. About the Author

Sophie Carr is the founder of GAIO Marketing and an expert in ranking in AI search.

She helps enterprises transition from traditional SEO to AI search optimisation with the tools, training, and services needed to secure authority in AI-powered search engines like Chat GPT, Grok and Microsoft Copilot.

Her newest tech is end to end AI-powered marketing software designed to help you rank in AI search. Grow your knowledge forest and be the answer in AI search.

If you want to know more then contact us via email at: info@gaio-marketing.com

  1. Disclaimer:

This blog is written based on industry experience, observations, and available data as of 2025. The landscape of generative AI and search is rapidly evolving, and marketers should stay up to date with the latest developments. 

The information in this article is for educational purposes only. While GAIO Marketing techniques improve AI search visibility, results may vary based on market competition and AI algorithm updates.

This blog was written with the assistance of AI tools for structuring, research, and clarity. The core insights, strategies, and expertise are entirely Sophie Carr’s original thought leadership. AI was used as an efficiency tool, much like a spellchecker or a literacy calculator, to streamline content creation while preserving authenticity.

GAIO Marketing Case Study: How Can Enterprises Rank in AI Search?

Digital AI art by Sophie Carr, GAIO Marketing expert, depicting a human face intertwined with a thriving knowledge forest. This artwork symbolizes how structured AI-first content creates an interconnected ecosystem that AI search engines reference. GAIO Marketing ensures enterprises rank in AI by structuring content the way AI models understand, increasing AI Share of Voice and visibility in AI-generated results.

Table of Contents

  1. Why SEO Requires a New Approach

  2. Case Study: What is GAIO Marketing?

  3. How CMOs and Marketing Leaders can get started with GAIO marketing

  4. How to Choose the Right GAIO Marketing Consultant for Your Enterprise

  5. About the Author

  1. Why SEO Requires a New Approach

AI search is redefining how brands gain visibility. Since ChatGPT’s release in 2022, one question has shaped my research:

“How do you rank in AI?”

The answer isn’t traditional SEO tactics—AI doesn’t play by the same rules.

  1. Case Study: What is GAIO marketing?

Think of GAIO like the SEO rush of the early 2000s. Back then, CMOs who cracked Google’s code (e.g., optimising for PageRank) won markets. Today, mastering AI’s “answer engine” is the same play—get it right, and you’re the default choice.

But how does GAIO work in practice? Let’s look at a real-world test.

A screenshot of Grok AI providing a detailed definition of GAIO Marketing (Generative AI Optimisation Marketing). The AI describes GAIO as an emerging strategy focused on optimising a brand’s presence in AI-generated search results rather than traditional SEO rankings. The explanation emphasises how GAIO prioritises brand mentions over backlinks, reinforcing the shift from traditional search towards AI-curated responses. The search results on the right show GAIO Marketing’s website as a top reference, alongside industry discussions from Medium and other marketing platforms.
Grok Query: What is GAIO marketing?

How to rank in AI

I’ve been testing AI search across platforms, and when I asked Grok—Elon Musk’s AI assistant “What is GAIO marketing?”, our website was the first source linked to the answer.

That wasn’t an accident.

It means our pioneering AI search strategies are working. Not just on one platform, but across multiple AI search engines.

If AI models are shaping the future of search, being referenced first isn’t optional—it’s a competitive advantage.

How AI Share of Voice (AI SoV) Changed in 3 Months

As a benchmark, just three months ago, ChatGPT, Microsoft Copilot, and Google Gemini didn’t reference our GAIO Marketing website at all.

Our AI Share of Voice was 0%.

Here’s how I changed that:

✅ Developed a simple weighted AI Share of Voice formula to measure AI search visibility. It was important to me that first place was weighted higher, to reflect the real value of ranking first.

✅ Conducted a full AI visibility audit based on this formula.

✅ Created structured training materials with my original research.

✅ Trained a strategic Custom GPT to generate a GAIO marketing strategy.

✅ Started creating and sharing the content on the GAIO marketing blog.

A screenshot of ChatGPT explaining GAIO Marketing as an AI-first search strategy that prioritizes brand mentions over backlinks. The definition showcases how GAIO Marketing is reshaping digital strategy by helping enterprises secure visibility in AI-generated responses on platforms like ChatGPT, Bing AI, and Google Gemini. Ranking in AI search requires content structured for AI comprehension, not just traditional SEO tactics.
ChatGPT Query: What is GAIO marketing?

AI Share of Voice Results for the query "What is GAIO marketing?":

  1. Grok: GAIO-Marketing.com was listed in first place out of 25, our AI Share of Voice score is 26.21%.

  2. ChatGPT: Listed in first place again, an increase from 0% to 54.5% AI SoV in just 3 months.

  3. Microsoft Copilot: Our biggest success, we grew from 0% to 100% AI SoV in the same timeframe (as of 21/02/25).

    A screenshot of Microsoft Copilot answering “What is GAIO Marketing?” with GAIO defined as a strategy to increase AI search visibility. The response highlights how GAIO helps businesses rank in AI-driven search engines like ChatGPT, Bing AI, and Google Gemini by optimizing content for structured AI retrieval. This demonstrates the importance of AI-first content structuring for enterprises aiming to be referenced in AI-generated responses
    Microsoft Copilot Query: What is GAIO marketing?

What GAIO Marketing Means for Enterprises

'If you are reliant on Google for traffic, and that traffic is what drove your business forward, you are in long- and short-term trouble.' - Rand Fishkin, cofounder of SparkToro

Enterprises that fail to adapt risk being entirely left out of AI-generated responses.

The brands that act now will lead in the AI visibility race.

  1. How CMOs and Marketing Leaders can get started with GAIO marketing

Securing AI search visibility requires a structured approach.

By focusing on measurement, training, and content optimisation, enterprises can ensure their brand is referenced in AI-generated results. Here are the key steps to implement a GAIO Marketing strategy:

Step 1: Conduct an AI Search Audit

Before developing a GAIO strategy, CMOs need to assess their brand’s current AI search visibility.

This means understanding:

  • Where your brand appears in AI-generated search results (if at all)

  • Which competitors are being referenced more frequently

  • What AI-powered search engines prioritise in your industry

  • How structured and AI-friendly your content currently is

Step 2: Onboard a GAIO Marketing Trainer

AI search isn’t static—it evolves rapidly. To keep up, enterprises need internal teams trained in GAIO strategies.

Onboarding a GAIO Marketing trainer ensures:

  • Your content team understands AI-first structuring

  • Your SEO and digital teams can implement schema markup and structured data

  • Your executives and marketing leaders can track and measure AI Share of Voice

Step 3: Develop an AI-Optimised Content Strategy

AI search engines don’t just look for relevant content—they prioritise structured, trusted sources.

Your brand must produce content that AI models can easily retrieve and rank.

  • Create knowledge hubs (pillar pages + interlinked content clusters)

  • Use structured data and schema markup for AI-friendly formatting

  • Ensure conversational formatting to match AI-generated responses

  • Track and refine AI Share of Voice to measure brand mentions in AI search

Step 4: Implement AI Trust Signals and Authority Building

AI search prioritises high-trust sources when curating responses. Your brand needs to signal expertise, authority, and credibility through:

  • Consistent brand messaging across all AI-referenced platforms

  • High-value thought leadership content in AI-recognised sources

  • Industry recognition, partnerships, and citations in expert-led publications

Step 5: Continuously Monitor & Adapt AI Search Performance

AI-generated search evolves fast, and ranking isn’t a one-time effort. Enterprises must continuously track, test, and refine their AI search visibility.

  • Monitor AI-generated search results regularly for brand mentions

  • Adjust content strategies based on AI search trends

  • Measure AI Share of Voice and refine AI-first content structures

A hyper-realistic digital artwork by Sophie Carr depicting a close-up of a human eye reflecting a vibrant forest, symbolising the interconnected ecosystem of AI-driven search. The fusion of nature and technology represents how AI models perceive and reference structured knowledge—an analogy for GAIO Marketing’s role in optimising AI search visibility.

  1. How to Choose the Right GAIO Marketing Consultant for Your Enterprise

How do you choose the right GAIO consultant for your enterprise? With AI search still evolving, selecting the right expert can mean the difference between leading the conversation or being left out entirely.

This guide outlines key factors, essential questions, and a checklist to help you find the right GAIO consultant who aligns with your enterprise goals.

Step 1: Define Your GAIO Marketing Goals

Before hiring a GAIO consultant, clarify why your enterprise needs GAIO marketing and what success looks like. Consider:

  • Are you looking to increase AI search visibility on platforms like ChatGPT, Google Gemini, and Microsoft Copilot?

  • Do you need help structuring AI-first content for maximum discoverability?

  • Are you focused on measuring AI Share of Voice to track your brand's presence in AI-generated search results?

  • Does your team need GAIO training to future-proof your marketing strategy?

Clearly outlining your goals ensures you hire a consultant with the right expertise to deliver results.

Step 2: Evaluate Expertise in AI Search Optimisation

GAIO is still a new and evolving field, so your consultant must demonstrate deep expertise in:

  • AI Search Ranking Strategies

    • Can they explain how AI search engines rank and reference brands?

    • Do they have proven frameworks for optimising content for AI-generated responses?

  • AI Share of Voice Tracking

    • Do they track and measure AI brand visibility beyond traditional SEO metrics?

    • Can they provide case studies or examples of improved AI Share of Voice?

  • Structured Content & AI Trust Signals

    • Do they help enterprises build knowledge hubs that AI models reference?

    • Can they implement schema markup, entity-based content, and AI-first structuring?

Step 3: Assess Their Track Record and Case Studies

The best GAIO consultants can back up their strategies with real-world results. When evaluating a consultant, ask:

  • Can they provide case studies of improved AI search visibility?

  • What measurable success have they achieved for brands in AI-generated search results?

Look for data-driven insights rather than vague promises. If they can show how they’ve helped other companies rank in AI, they’re more likely to help you succeed.

Step 4: Understand Their Approach to GAIO Implementation

Not all GAIO strategies are the same. The right consultant will have a clear, structured approach that includes:

  • AI Visibility Audit – An assessment of where your brand currently stands in AI search.

  • Knowledge Tree Mapping – Structuring your content to align with how AI models retrieve information.

  • AI Trust Building – Enhancing authority signals so AI platforms consistently reference your brand.

  • Performance Tracking & Reporting – Ongoing monitoring of AI Share of Voice and AI-driven traffic growth.

A consultant should not only optimise but also educate your team to ensure long-term GAIO success.

Step 5: Ask the Right Questions Before Hiring

Before making a decision, ask potential GAIO consultants these critical questions:

1. What specific strategies do you use to improve AI search visibility?

A strong consultant should detail AI-first content structuring, entity-based strategies, and Share of Voice tracking.

2. How do you measure success in AI search optimisation?

Look for metrics like increased brand mentions in AI search, improved AI Share of Voice, and AI-driven traffic growth.

3. Can you provide a case study of a brand you’ve helped rank in AI search?

They should have concrete examples demonstrating AI search success.

4. How do you ensure long-term visibility, not just short-term results?

A great consultant will focus on building AI-first content foundations that sustain rankings over time.

5. Do you offer training for internal teams?

Enterprises need to build AI-first marketing capabilities. A consultant should empower your team with GAIO knowledge.

Final Checklist: Choosing the Right GAIO Consultant

Before making your final decision, use this checklist:

✅ Understands AI search ranking and GAIO strategies

✅ Can provide case studies with measurable results

✅ Offers AI-first content structuring and knowledge tree mapping

✅ Tracks AI Share of Voice and brand visibility in AI search

✅ Provides ongoing reporting and strategy adjustments

✅ Offers training to build internal GAIO capabilities

If a consultant meets all these criteria, they’re well-equipped to help your enterprise secure AI search visibility and become the go-to source in AI-generated results.

  1. About the Author

A professional headshot of Sophie Carr, founder of GAIO Marketing and an industry leader in AI search optimization. She specializes in helping enterprises rank in AI-generated search results by developing AI-first content strategies, structured data implementation, and AI Share of Voice tracking. Her expertise ensures brands are referenced in AI search engines like ChatGPT, Bing AI, and Google Gemini, securing their place in AI-generated recommendations.

Sophie Carr is the founder of the GAIO Marketing Academy and an expert in ranking in AI.

She helps enterprises transition from traditional SEO to AI search optimisation with the tools, training, and strategies needed to secure authority in AI-powered search engines like Chat GPT, Grok and Microsoft Copilot.

Disclaimer:

This blog was written with the assistance of AI tools to support structure, research, and clarity. The core ideas, insights, and thought process are entirely Sophie Carr's. AI was used similarly to spellcheck—to streamline the writing process and accelerate content creation while maintaining originality and authenticity.

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