AI Share of Voice (AI SoV): How to measure your brand’s presence in AI search

AI-generated search results are changing the way brands compete for visibility. Instead of traditional SEO rankings, businesses now need to track how often they appear in AI-driven responses from platforms like ChatGPT, Microsoft Copilot, Google Gemini, and Grok.

This is where AI Share of Voice (AI SoV) comes in.

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Table of Contents

1. AI share of voice (AI SoV) defined

2. Why AI share of voice matters

3. Why AI share of voice should be weighted

4. How to calculate AI share of voice for one query on one AI platform

5. How to calculate AI SoV for one query across multiple AI platforms

6. Final thoughts

7. About the author

8. Disclaimer

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1. AI share of voice (AI SoV) defined

AI SoV is a percentage-based score that measures how frequently an AI model mentions your brand compared to competitors in response to a specific query.

Think of it like a market share metric, but instead of tracking revenue or customer reach, it tracks AI-driven visibility. The higher your AI SoV, the more AI models reference your brand as an authoritative source. The more influence you have.

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2. Why AI share of voice matters

AI-generated search is rapidly influencing purchasing decisions, and being referenced by AI platforms can directly impact your brand’s success. A strong AI SoV brings measurable benefits:

• More website visitors - Higher visibility in AI-generated search leads to increased organic traffic.

• Better quality leads - AI recommendations position your brand in front of relevant audiences actively seeking solutions.

• Higher sales conversions - Customers trust AI-driven answers, increasing the likelihood of conversions.

• Stronger brand authority - Consistent AI mentions reinforce your brand as an industry leader.

• Competitive advantage - Tracking AI SoV helps you stay ahead of competitors in emerging AI search trends.

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3. Why AI share of voice should be weighted

Unlike traditional Share of Voice calculations, where each mention is counted equally, AI-generated search results require a weighted approach.

Here’s why:

1. Different AI platforms list different numbers of brands – One AI model might only mention a single company, while another lists 20.

2. Ranking order matters – Being the first brand mentioned in an AI-generated response carries more influence than being third or tenth.

3. A standardised method is needed – A simple, scalable system allows fair comparisons regardless of how many brands are listed.

This is why we use a reciprocal weighting system (1/place) for AI SoV. This method ensures that each brand’s visibility is fairly represented, no matter how many brands an AI model includes.

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4. How to calculate AI share of voice for one query on one AI platform

Recommendation: Focus on generic queries (where multiple brands could be mentioned) for a more meaningful competitive SoV

Let’s say you ask ChatGPT: “What’s the best online broker for international investors?” and receive this ranking:

1. Brand A

2. Your Brand

3. Brand C

4. Brand D

To calculate your weighted AI SoV:

1. Give the place a value, e.g. 1st = 1, 2nd = 2, 3rd = 3 and so on.

2. Assign a weight to each position using the formula 1/place value:

   • 1st place = 1.00 (1/1)

   • 2nd place = 0.50 (1/2)

   • 3rd place = 0.33 (1/3)

   • 4th place = 0.25 (1/4)

3. Identify your brand’s weighted score:

   • Your brand is in 2nd place, so your score is 0.50.

4. Add up all weighted scores:

   • 1.00 (Brand A) + 0.50 (Your Brand) + 0.33 (Brand C) + 0.25 (Brand D) = 2.08

5. Calculate your AI SoV:

   • (Your Brand’s Weighted Score ÷ Total Weighted Mentions) × 100

   • (0.50 ÷ 2.08) × 100 = 24.0% AI SoV

This means your brand holds 24% of the AI-generated response share for this query on ChatGPT.

Competitor benchmarking table for ChatGPT response (4 brands mentioned)

Brand	Position Value	Weighted Score	AI SoV (%)
Brand A	1	1.00	48.0%
Your Brand	2	0.50	24.0%
Brand C	3	0.33	16.0%
Brand D	4	0.25	12.0%
Total Weighted Mentions		2.08	100.0%

Key Insight: Brand A is winning AI search responses for this query, meaning your brand needs to improve authority signals or optimise content to increase AI visibility.

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5. How to calculate AI SoV for one query across multiple AI platforms

When measuring AI Share of Voice (AI SoV) across multiple AI platforms, the number of brands mentioned can vary significantly between responses. This means we need to apply the same weighted SoV calculation separately for each platform before averaging the results.

Here’s how to do it step by step:

Step 1: AI SoV calculation for each AI platform

For example, let’s say we ask the same query to different AI models:

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Grok response (5 brands mentioned)

Brand	Position Value	Weighted Score	AI SoV (%)
Brand B	1	1.00	43.8%
Your Brand	2	0.50	21.9%
Brand X	3	0.33	14.6%
Brand Y	4	0.25	10.9%
Brand Z	5	0.20	8.8%
Total Weighted Mentions		2.28	100.0%

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Microsoft copilot response (2 brands mentioned)

Brand	Position Value	Weighted Score	AI SoV (%)
Brand C	1	1.00	66.7%
Your Brand	2	0.50	33.3%
Total Weighted Mentions		1.50	100.0%

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Google Gemini response (7 brands mentioned)

Brand	Position Value	Weighted Score	AI SoV (%)
Your Brand	1	1.00	38.6%
Brand A	2	0.50	19.3%
Brand C	3	0.33	12.9%
Brand B	4	0.25	9.6%
Brand X	5	0.20	7.7%
Brand Y	6	0.17	6.4%
Brand Z	7	0.14	5.5%
Total Weighted Mentions		2.59	100.0%

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Step 2: Create an AI SoV master score table

Once we have calculated AI SoV for each platform, we can compare overall rankings for all brands.

AI SoV master score table

Brand	ChatGPT SoV	Grok SoV	Microsoft Copilot SoV	Google Gemini SoV	Average AI SoV
Your Brand	24.0%	21.9%	33.3%	38.6%	29.4%
Brand A	48.0%	0%	0.0%	19.3%	16.8%
Brand B	0.0%	43.8%	0.0%	9.7%	13.4%
Brand C	16.0%	0.0%	66.7%	12.7%	23.9%
Brand D	12.0%	0.0%	0.0%	0.0%	3.0%
Brand X	0.0%	14.6%	0.0%	7.7%	5.6%
Brand Y	0.0%	10.9%	0.0%	6.4%	4.3%
Brand Z	0.0%	8.8%	0.0%	5.6%	3.6%
Sum	100.00%	100.00%	100.00%	100.00%	100.00%

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Step 3: Final AI SoV ranking order & strategy

Here’s the final ranking based on overall AI SoV:

1. Your Brand – 29.4%

2. Brand C – 23.9%

3. Brand A – 16.8%

4. Brand B – 13.4%

5. Brand X – 5.6%

6. Brand Y – 4.3%

7. Brand Z – 3.6%

8. Brand D – 3.0%

This ranking shows who is leading in AI visibility and who needs to improve. In this case, your brand is currently in first place overall, but competitors like Brand C and Brand A are still close behind.

By targeting weaker-performing platforms like Grok and ChatGPT, you can increase your AI visibility and ensure your brand is referenced more often in AI-generated search results.

This approach ensures a practical, real-world way to measure AI visibility across multiple AI models, giving you clear insights into where to focus your GAIO strategy.

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6. Final Thoughts

Tracking AI Share of Voice is essential in a world where AI-generated search influences how businesses and consumers find information. AI SoV provides a clear, data-driven way to measure your brand’s AI visibility and compare it against competitors.

By understanding which AI platforms mention your brand the most and identifying gaps in visibility, you can fine-tune your AI-optimised content strategy to improve brand authority and increase your presence in AI-generated search results.

If you’d like an AI visibility audit to measure your brand’s performance across AI search platforms, contact us. We can help you gain the insights needed to enhance your AI presence and ensure your brand remains a top reference in AI-generated results.

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7. About the author

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

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.

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8. Disclaimer

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.

AI-Optimised Search: The Essential Guide for Business Leaders

Table of Contents

1. The Quiet Shift in Search—And Why Enterprises Can’t Afford to Ignore It

2. Why Enterprises Are Losing Visibility in AI Search

   • AI Search Doesn’t Work Like Traditional Search Engines

   • Conversational Search Is Reshaping Enterprise Visibility

   • AI Search Rewards Depth and Consistency

3. The Stakes Are High—And Most Enterprises Aren’t Prepared

4. What CMOs and Marketing Leaders Need to Consider

5. About the Author

6. 7 FAQs on AI Search Optimisation & Enterprise Strategy

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1. The Quiet Shift in Search—And Why Enterprises Can’t Afford to Ignore AI Search Optimisation

For decades, search visibility was a game of keywords, backlinks, and domain authority. Businesses knew how to compete. Marketers had clear rules to follow. SEO was an art and a science, a dance with an algorithm and relatively predictable.

'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

That era is changing. AI search is redefining how brands are discovered, but most enterprises haven’t adjusted their strategies yet.

AI-powered search engines like ChatGPT, Google Gemini, and Bing AI no longer return a ranked list of links. Instead, they curate direct responses, drawing from structured, high-quality sources to deliver the most relevant answer.

This shift presents a fundamental challenge: if your brand’s content isn’t structured, credible, and AI-friendly, you may not be part of the conversation at all.

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2. Why Enterprises Are Losing Visibility in AI Search

The brands that once dominated search are waking up to a new reality: their visibility is slipping.

When senior decision-makers use AI-powered search to research solutions, they don’t scroll through pages of results. They expect clear, authoritative answers. The question is: will your brand be included in those responses?

Here’s why many enterprises are struggling to maintain AI search visibility:

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2.1 AI Search Doesn’t Work Like Traditional Search Engines

Traditional search engines ranked content based on a mix of backlinks, keyword usage, and domain authority. However, AI-generated search responses don’t follow the same ranking principles. Instead, AI platforms prioritise:

• Structured content that presents clear, well-organised information

• Authoritative, high-trust sources rather than sheer keyword density

• Context and relevance in response to natural language queries

If your brand’s content isn’t structured in a way that AI can process and reference, your visibility will decline—even if your SEO is strong.

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2.2 Conversational Search Is Reshaping Enterprise Visibility

Executives aren’t typing static keyword queries anymore. They’re asking AI assistants natural-language questions like:

❌ Old search: "best enterprise AI solutions"

✅ AI search: "Which AI solutions are most effective for large enterprises?"

AI-powered platforms favour brands that answer complex, intent-driven queries with structured, digestible content.

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2.3 AI Search Rewards Depth and Consistency

One of the biggest shifts AI search has introduced is how it determines authority. While traditional SEO relied heavily on backlinks, AI-powered search engines prioritise content depth, consistency, and cross-platform relevance.

Rather than simply looking at inbound links, AI models assess:

✅ Content Depth – Is your content comprehensive, well-structured, and answering real customer questions? AI ranks sources that provide rich, meaningful insights over surface-level keyword stuffing.

✅ Consistency Across Platforms – Does your brand provide a unified narrative across its website, social media, and other digital assets? AI prefers brands that reinforce their expertise across multiple sources.

✅ Engagement & Validation – Does your content align with widely accepted industry knowledge, appear in AI-curated responses, or contribute to broader discussions in your field? AI prioritises content that demonstrates sustained relevance and expertise, ensuring that enterprises with strong knowledge leadership remain visible.

For enterprises, this means shifting focus from just ranking pages to ensuring their content is recognised as a trusted source of knowledge in AI-generated results.

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3. The Stakes Are High—And Most Enterprises Aren’t Prepared

This shift in search isn’t hypothetical. It’s happening now.

• 95% of business leaders plan to use AI-powered search tools in their decision-making process over the next 12 months (Forrester).

• According to MIT Technology Review, AI-generated search is accelerating the trend of zero-click searches, where users get answers without visiting external websites. As Rand Fishkin, cofounder of SparkToro, warns, '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.' Enterprises that fail to adapt risk losing a significant share of their organic visibility (MIT Technology Review).

• AI-generated search is not just shifting visibility—it’s redefining influence. Enterprises that fail to adapt will not only lose organic traffic but risk becoming invisible in key industry conversations, missing out on shaping narratives, building trust, and driving high-value business opportunities.

The challenge is ensuring that your brand is recognised as a credible source of information in AI-generated search results.

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4. What CMOs and Marketing Leaders Need to Consider

If enterprises want to maintain digital visibility, they need to rethink their approach to content and invest in their teams. This means:

✅ Training marketing leaders and teams to understand AI search optimisation, structured content strategies, and AI-first content best practices.

✅ Measuring AI Share of Voice to track how often (and where) your brand is referenced in AI search, ensuring consistent presence in AI-generated responses.

✅ Investing in AI-first content structures that align with how AI models retrieve and process information.

✅ Building authoritative knowledge hubs instead of isolated content pieces to reinforce expertise across platforms.

For now, one thing is clear: the brands that take AI search seriously now will be leading the AI conversations in the future.

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7. About the Author

Sophie Carr is the founder of GAIO Marketing and a recognised expert in AI-first search optimisation.

She helps brands build knowledge clusters that AI tools trust and reference—ensuring businesses stay visible in an increasingly AI-driven world.

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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8. 7 FAQs on AI Search Optimisation & Enterprise Strategy

8.1 How can my marketing team adapt to AI search ranking changes?

AI search ranking prioritises structured, high-authority content rather than traditional SEO tactics like backlinks and keyword density. To stay visible, marketing teams need to focus on AI-first content structuring, ensuring that their information is easily interpreted and referenced by AI models. This involves using schema markup, conversational search optimisation, and entity-based content clustering to align with AI-generated search responses.

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8.2 What is GAIO, and how does it differ from traditional SEO?

GAIO (Generative AI Optimisation) is designed specifically for AI-driven search engines. While traditional SEO focuses on ranking webpages, GAIO ensures that content is understood, structured, and referenced by AI models like ChatGPT, Google Gemini, and Bing AI. Instead of optimising for keyword-based rankings, GAIO helps brands establish AI-friendly authority, making them a trusted source in AI-generated responses.

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8.3 How can enterprises measure their AI Share of Voice?

AI Share of Voice (AI SoV) measures how often a brand is referenced in AI-generated search results. Unlike traditional SEO metrics, which track organic search traffic and rankings, AI SoV focuses on brand presence within AI-curated answers. Enterprises can monitor this by:

• Tracking brand mentions in AI-powered search results

• Analysing response accuracy and relevance in AI-generated content

• Benchmarking competitor visibility in AI search responses

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8.4 What content structures work best for AI search optimisation?

AI search engines favour structured, well-organised content over unstructured information. The most effective approaches include:

• Knowledge Hubs: Organising content into pillar pages with linked subtopics for depth.

• Entity-Based Content: Aligning content with known industry topics and AI knowledge graphs.

• Conversational Format: Using question-answer structures that match how AI models process and retrieve data.

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8.5 How do AI-powered search engines determine authority in my industry?

Authority in AI search isn’t just about domain reputation—it’s about being a consistent, structured, and validated source of information. AI models assess:

• Content depth and structure (Does it provide complete, well-organised insights?)

• Cross-platform consistency (Is the same messaging reflected across websites, reports, and media?)

• Third-party credibility (Is the brand referenced in industry reports, case studies, or high-trust sources?)

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8.6 What practical steps can my team take to future-proof our digital strategy?

As AI-generated search continues to evolve, teams should focus on long-term adaptability by:

• Investing in structured data and content formatting that AI models favour.

• Developing AI-friendly authority signals through strategic partnerships and industry collaboration.

• Regularly testing AI search visibility by tracking how AI-generated answers reference the brand.

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8.7 Where do we start if we want to implement GAIO across our organisation?

Adopting GAIO requires a shift in how enterprises approach content strategy. The best starting points are:

• Conducting an AI visibility audit to assess current search presence.

• Re-structuring high-value content for AI consumption, using knowledge hubs and schema markup.

• Training internal teams on how AI search impacts content production and distribution.

By shifting from traditional keyword-based SEO to structured, AI-first content strategies, enterprises can stay ahead in AI search and ensure long-term digital visibility.

AI Ranking Optimisation: How to Get Featured in AI-Generated Search Results

AI usage has skyrocketed since the release of ChatGPT—and it’s only getting faster. At the recent Europe AI Action Summit 2025, the EU announced a €200 billion investment into AI innovation. With 12 AI Factories already live and AI Gigafactories on the way, we’re entering a new era of AI-first search.

This shift marks a huge opportunity for marketers who understand how generative AI works. 95% of buyers plan to use GenAI in their decision-making process in the next 12 months (Forrester). If you want your content to show up in AI-driven search results, now is the time to adapt.

Here's how you can position your content to get featured.

Table of Contents

1. How Do I Rank in AI-Generated Search Results?

2. How to Build Knowledge Clusters to Rank in AI Search

3. Optimising Content for AI Search Rankings

4. Building Trust to Rank Higher in AI Search

5. Monitoring Your AI Search Rankings Over Time

6. Final Thoughts

7. Discussion Point

8. About the Author

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1. How Do I Rank in AI-Generated Search Results?

AI search tools like ChatGPT, Google Gemini, and Bing AI don’t just mirror Google’s search rankings. These tools use advanced language models to find clear, authoritative answers to user questions.

Here’s what matters most:

• Relevance: AI prioritises content that aligns with user intent, entity relationships, and semantic search.

• Trust: AI favours brands with authoritative citations, PR mentions, and third-party endorsements.

• Structure: AI processes structured data (schema markup, metadata, and Knowledge Trees) to organise information.

• Freshness: AI rewards content that is frequently updated, time-sensitive, and newsworthy.

• Redundancy: AI deprioritises repetitive or low-value content that lacks new insights.

Tip: Run an AI Visibility Audit to see how often your content appears in AI-generated responses.

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2. How to Build Knowledge Clusters to Rank in AI Search

Generative AI looks for patterns across related content. If your content stands alone, it’s less likely to be seen as authoritative.

That's why you should create knowledge clusters - or as I like to call them: GAIO Knowledge Trees.

The GAIO Knowledge Tree:

AI search thrives on structured, interconnected content—just like a tree.

• The ground represents your core category.

• The trunk is the key question your audience asks.

• The branches are the content pieces answering that question.

• The leaves are supporting resources like videos, infographics, or case studies.

• The roots are the links connecting your content in your backlink strategy.

AI models favour brands that create clear, knowledge-rich ecosystems like GAIO Knowledge Trees—not disconnected content silos. As they are all organised in a category, a group of GAIO Knowledge Trees that share the same ground, you can consider this cluster a GAIO Knowledge Forest.

This GAIO strategy visualisation helps enterprises structure these clusters and answer real audience questions, building authority in your space and increasing your AI visibility share of voice score.

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3. Optimising Content for AI Search Rankings

AI-first search demands more than surface-level optimisation. Here’s how to get AI tools to notice your content:

• Use Schema Markup: Help AI understand context through structured data.

• Answer Questions Directly: Write content that mirrors how users phrase questions.

• Keep Content Fresh: AI rewards updated, accurate information.

Tip: Think like your customer. Write content as if you’re having a conversation and answering their question directly.

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4. Building Trust to Rank Higher in AI Search

The EU AI Action Summit stressed that safety, accuracy, and trust are central to Europe's AI strategy. The same principles apply to your content.

Here’s how you can build AI-friendly trust:

• Cite Industry Sources: Reference reliable publications and research.

• Earn Authoritative Backlinks: Partner with industry leaders for collaborations.

• Showcase Expertise: Add author bios, case studies, and data sources to your posts.

Fact: The EU’s €200 billion AI investment signals long-term growth. AI isn’t going anywhere—start optimising your content for the new search ecosystem now to win in this space.

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5. Monitoring Your AI Search Rankings Over Time

AI search is evolving rapidly. Regular monitoring helps you stay ahead.

Key metrics to watch:

• AI Mentions: Track how often your content is referenced in AI tools like Bing AI using the AI Share of Voice formula.

• Performance of Knowledge Clusters: Identify which clusters are gaining visibility.

• Emerging User Questions: Keep an eye on shifting trends to maintain relevance.

GAIO Marketing tools can help track these metrics with detailed AI visibility reports.

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6. Final Thoughts

Generative AI is becoming the go-to for search. The EU's substantial investment in AI infrastructure signals that AI search is here to stay. As these tools continue to evolve, brands that invest in knowledge clusters and value-driven content will dominate AI-generated search results.

The opportunity is clear: adapt your content now to get ahead, or risk being left behind.

Ready to optimise your content for AI search?

Learn more about GAIO Marketing and how we help brands stay visible in the age of AI.

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7. Discussion Point

How is your brand preparing to rank in AI-generated search results?

Share your thoughts in the comments below!

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8. About the Author

Sophie Carr is the founder of GAIO Marketing and a recognised expert in AI-first search optimisation.

She helps brands build knowledge clusters that AI tools trust and reference—ensuring businesses stay visible in an increasingly AI-driven world.

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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.