AI and SEO: The Future of Search Optimisation

So, what’s really happening with AI and SEO? If you’ve noticed your traffic dropping but your conversion rates climbing, you’re witnessing the shift firsthand.

Key insights

• AI automates time-consuming SEO tasks like keyword research, competitor analysis, and schema markup generation, freeing marketers to focus on strategy.
• Content optimisation now requires structure for AI parsability, with clear headings, direct answers, and conversational language that helps search engines understand context and intent beyond simple keyword matching.
• Answer Engine Optimisation (AEO) is replacing traditional SEO as the priority shifts from ranking for keywords to providing comprehensive answers that AI platforms cite in generated responses.
• AI-powered personalisation is transforming search results, analysing how users interact with websites and tailoring content to individual preferences, making user experience a critical ranking factor.
• Higher conversion rates offset lower traffic volume as users finding content through AI answer engines are further along in their research and ready to act, making quality more valuable than quantity.

What is AI SEO?

AI SEO is the practice of optimising your content so it’s visible and citable in AI-powered search experiences. Think Google’s AI Overviews, AI Mode, and Microsoft’s Copilot Search. It’s not a replacement for traditional SEO. It’s an evolution.

Two types of AI in SEO

When we talk about AI and SEO, we’re really talking about two different things:

1. AI-powered SEO tools that help you work faster and smarter. These platforms use machine learning to analyse keywords, predict trends, and automate content optimisation.
2. AI-driven search engines that generate answers instead of just ranking links. Google’s AI Overviews now appear in approximately 30% of US search results and have rolled out across Europe. Microsoft’s Copilot Search is deeply integrated into the Microsoft 365 ecosystem, blending internal work data with public web results.

Why this matters now

AI isn’t optional anymore. It’s fundamental to visibility. The presence of an AI Overview on a search results page can lead to a 70% drop in organic click-through rates, (source). If your content isn’t structured, authoritative, and parsable by AI, you’re invisible in the one place users are actually looking: the answer itself.

For B2B marketers, this shift is particularly critical. Your content isn’t just competing on Google anymore. It’s competing to be the trusted source that shows up when a procurement manager asks Copilot for vendor recommendations.

How AI is transforming SEO right now

From keywords to search intent

The old model was simple: find keywords with high volume, optimise for them, rank, and get traffic. That’s no longer enough. AI doesn’t just match keywords. It interprets context and intent.

When someone searches “best CRM for small business,” AI understands they’re not looking for a dictionary definition. They want comparisons, pricing, and real-world use cases. If your content only targets the keyword without addressing the underlying question, you won’t surface in AI-generated answers.

This shift means:

• Context matters more than keyword density. AI evaluates whether your content genuinely answers the question behind the query.
• Semantic relevance is the new ranking factor. Related terms, natural phrasing, and comprehensive coverage signal authority.
• User intent defines visibility. Informational, navigational, transactional, and commercial queries each require different content approaches.

Understanding this distinction is critical. If you’re still optimising for traffic volume without considering intent, you’re competing in a fragmented ecosystem where platforms like ChatGPT, Google AI Overviews, and AI Mode only agree on their recommendations about 17% of the time, (source).

For a deeper dive into how search intent is reshaping visibility, see our guide on Search Intent and AI: Why your clicks are dropping.

Zero-click searches and answer engines

Here’s the uncomfortable truth: zero-click searches are projected to exceed 70% of all queries in 2025. Most users never leave the results page because AI has already given them the answer.

Google’s AI Overviews synthesise information from multiple sources and display it at the top of the SERP. Microsoft’s Copilot does the same in Bing and across the Microsoft 365 suite. The traditional “ten blue links” model is effectively over.

What this means for your traffic:

• The presence of an AI Overview can lead to a 70% drop in organic click-through rates
• Globally, around 60% of all Google searches now end without a click, with the figure approaching 75% on mobile devices, (source).

But here’s the opportunity:

Referral traffic from generative AI platforms like ChatGPT demonstrates significantly higher conversion rates than traditional Google search traffic. The traffic that does come through is more qualified, further down the funnel, and ready to act.

The strategy isn’t to mourn lost clicks. It’s to become the authoritative source AI cites, while also capturing the high-intent users who do click through. This is the core shift explored in our article on how AI and SEO is Reshaping Digital Marketing.

Generative Engine Optimisation (GEO)

If SEO is about ranking in search results, Generative Engine Optimisation (GEO) is about being featured in AI-generated answers. It’s a new discipline, and it complements traditional SEO rather than replacing it.

How GEO differs from SEO:

Traditional SEO	Generative Engine Optimisation (GEO)
Optimises for ranking position	Optimises for citation frequency
Focuses on clicks and traffic	Focuses on being the source AI references
Keyword-centric content	Answer-centric, conversational content
Success measured by rank	Success measured by visibility in AI responses

Key GEO strategies include:

1. Creating comprehensive, authoritative content that directly answers complex questions
2. Using structured data to help AI models understand your content’s context
3. Building topical authority so AI recognises you as a primary source
4. Ensuring content is parsable with clear headings, lists, and concise language

At Roar Digital, we’ve developed a dedicated approach to help UK businesses adapt. Learn more about Generative Engine Optimisation services.

Core benefits of AI for SEO

AI isn’t just changing how search engines work. It’s fundamentally improving how marketers research, create, and optimise content.

Smarter keyword research

AI tools can analyse vast datasets to identify relevant, high-potential keywords faster than any manual process. They don’t just surface search volume. They interpret user intent behind searches, helping you understand what people actually want when they type a query.

What this looks like in practice:

• Machine learning identifies semantic relationships between keywords, revealing topic clusters you might have missed.
• Predictive algorithms forecast emerging trends before they peak, letting you create content proactively.
• Natural language processing interprets conversational queries, helping you optimise for voice search and AI Mode’s multimodal capabilities.

So instead of chasing keywords, you’re anticipating needs.

Automated Content Optimisation (ACO)

AI can help generate, refine, and structure content at scale. But there’s a critical caveat: Google’s official guidance is firm. The focus is on rewarding original, high-quality, people-first content that demonstrates Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T), regardless of how it’s produced.

Using AI primarily to manipulate search rankings violates Google’s spam policies. Using it to augment human expertise? That’s the smart play.

How to use AI responsibly:

1. Draft and research – Use AI for initial content drafts, topic ideation, and summarisation.
2. Human oversight – Fact-check every claim. Add firsthand experience and original insights that AI can’t replicate.
3. Technical optimisation – AI can generate schema markup, suggest meta descriptions, and identify content gaps.

The key differentiator is the “Experience” component of E-E-A-T. AI cannot have genuine, real-world experience. Content demonstrating firsthand knowledge carries significant advantages because it provides value AI cannot replicate on its own.

Technical SEO enhancements

AI streamlines the technical foundations that make content discoverable and parsable.

Schema markup and structured data:

Schema.org has evolved from a tool for rich snippets to a foundational communication layer for AI. It provides explicit, machine-readable context about your content, helping AI models understand entities, properties, and relationships. This is critical for the Retrieval-Augmented Generation (RAG) systems powering most AI answer engines.

By marking up content with types like FAQPage, Article, Product, or Organisation, you provide clear signals that help AI confidently select your content for inclusion in generated responses.

Site speed and crawlability:

AI-powered crawlers prioritise content that loads quickly and is structured logically. Microsoft’s Bing has been particularly explicit about this, promoting real-time indexing through the IndexNow protocol and highlighting the <lastmod> tag in sitemaps as a critical freshness signal.

Predictive SEO

AI’s ability to forecast trends is perhaps its most strategic advantage. Instead of reacting to changes in search behaviour, you can anticipate them.

Predictive capabilities include:

• Forecasting seasonal trends and user needs before they peak
• Identifying content gaps in your niche that competitors haven’t filled
• Predicting which topics will gain traction based on early signals in search data

Gartner forecasts that AI agents will augment or automate 50% of all business decisions by 2027, (source). The winners will be those who use AI to move faster and smarter than their competition.

Personalised user experiences

AI helps tailor content and user journeys to individual preferences, which can boost engagement and improve rankings. Google’s AI Mode, powered by the Gemini 2.5 model, offers hyper personalised search experiences incorporating signals from a user’s Gmail and Calendar activity.

This means the concept of a single, objective ranking for a given keyword is becoming meaningless. The answer is tailored to the individual’s real-time personal situation. Traditional rank tracking as a primary KPI is being invalidated. The new metric is citation frequency and presence within personalised AI-generated answers.

Technical foundations for AI SEO success

Content quality matters, but without the right technical foundation, even brilliant content stays invisible. AI-powered search engines need clear signals to find, understand, and trust your content. As of September 2025, a notable divergence has emerged between Google and Microsoft’s technical priorities, requiring a dual approach.

Schema markup and structured data

Schema.org has evolved from a tool for enabling rich snippets to the foundational communication layer for AI. It provides explicit, machine-readable context about your content, helping AI models understand entities, their properties, and their relationships.

Why schema matters for AI:

Structured data is critical for the Retrieval-Augmented Generation (RAG) systems powering most AI answer engines. RAG systems retrieve relevant information from a knowledge base (like the web) before generating an answer. Schema markup makes that retrieval process faster and more accurate.

Key schema types for AI visibility:

• FAQPage: Marks up question-and-answer content, making it easy for AI to extract direct answers.

• Article: Provides context about authorship, publication date, and article structure.

• Product: Helps AI understand pricing, availability, and reviews for e-commerce content.

• Organisation: Establishes your business identity and builds trust signals.

While Google’s documentation notes it doesn’t support every property on Schema.org, it confirms its systems make general use of the vocabulary to understand content and enable future search features.

Google vs. Bing: Dual SEO strategy

The technical divide between Google and Microsoft has never been clearer. Each platform prioritises different signals, and UK businesses need to account for both.

Google’s holistic approach

Google’s official documentation for appearing in AI features like AI Overviews and AI Mode is deliberately broad. No special markup or files are needed beyond existing SEO fundamentals. To be eligible for inclusion, a page simply needs to be indexed and eligible to appear in search with a snippet.

Google’s recommended best practices:

1. Create helpful, people-first content that demonstrates E-E-A-T
2. Ensure your site is crawlable via robots.txt
3. Use a logical internal linking structure
4. Provide a good page experience (fast load times, mobile-friendly design)

Google appears confident in its advanced algorithms to holistically understand content quality and relevance without needing explicit, real-time signals.

Bing’s freshness and speed priority

Microsoft’s Bing has been particularly vocal about the technical signals it values for AI search, creating a more explicit and transparent system.

Two critical elements:

1. IndexNow

Bing strongly recommends adopting the IndexNow protocol. This open standard allows websites to instantly notify participating search engines whenever content is created, updated, or deleted. In an AI-driven search environment where real-time information is crucial, IndexNow provides a direct line of communication to ensure content freshness.

2. Sitemap <lastmod> Tag

Bing’s AI crawlers use the <lastmod> timestamp in XML sitemaps as a primary signal to prioritise which URLs to recrawl. An accurate and consistently updated lastmod value helps Bing focus its crawl budget on content that has actually changed, increasing the efficiency of indexing and ensuring the latest version of a page is available to the AI model.

Bing has explicitly stated that other tags like <changefreq> and <priority> are ignored.

Technical Element	Google	Bing
Schema markup	General use for understanding content	Recommended for context
IndexNow protocol	Not officially supported	Strongly recommended
Sitemap <lastmod>	Optional, no explicit priority	Critical freshness signal
Content freshness	Holistic quality assessment	Real-time signaling preferred
Technical philosophy	Algorithm-driven, broad signals	Transparent, explicit signals

For UK businesses where Bing holds a non-trivial market share, this necessitates a dual technical SEO strategy: continued focus on holistic content quality and semantic relevance for Google, coupled with robust, real-time signaling (IndexNow and accurate sitemaps) for Bing.

Need help implementing this dual strategy? Our SEO services are designed specifically for UK businesses navigating this fractured landscape.

Content built for parsability

Beyond metadata and protocols, the structure of the content itself is a critical technical factor. AI models that synthesise information from multiple sources favor content that is organised and easy to parse.

Best practices for parsable content:

• Use clear, hierarchical HTML structures: Proper use of heading tags (<h1>, <h2>, <h3>) helps AI understand content hierarchy.
• Leverage lists and tables: Bulleted lists, numbered lists, and data tables make information extraction straightforward.
• Write concisely: Short paragraphs and direct language that answers questions early in the text are highly effective for being featured in snippets and AI Overviews.
• Front-load answers: AI prefers content that provides the answer upfront, then elaborates with context.

Think of it this way: if a human can quickly scan your page and extract key information, AI can too.

The future of SEO: What’s next?

The trajectory is clear: search is moving from answering questions to completing tasks. The next 24 to 36 months will bring fundamental changes in how users discover information and how businesses compete for attention.

From ranking to being the answer

The primary objective of SEO is shifting. Instead of aiming for the number one position in a list of blue links, the goal is to become a trusted, authoritative source that AI features and cites within generated answers.

Success is no longer measured by rank position but by metrics like:

• Citation frequency: How often your content is referenced in AI-generated responses.
• Impression share in AI results: Your visibility across multiple AI platforms.
• Source authority: Whether AI models recognise you as a primary source for your topic.

This shift is compounded by fragmentation. A study comparing brand mentions across ChatGPT, Google AI Overviews, and AI Mode found that platforms only agreed on their recommendations for about 17% of queries. This lack of consensus means a single-engine strategy is no longer viable.

What this requires:

1. Build broad topical authority across multiple AI ecosystems
2. Create content that AI recognises as comprehensive and trustworthy
3. Focus on being the primary source, not just another voice covering the same topic

The businesses that win will be those producing proprietary research, original case studies, and expert insights drawn from lived experience. As AI makes surface-level content a near-zero-cost commodity, its value plummets. The new premium is on content AI cannot easily generate.

AI + Local SEO

Local search is being transformed just as dramatically as general search. AI Overviews are now replacing the traditional local map pack for certain “near me” queries, instead showing summarised local business information synthesised from multiple sources.

What’s changing:

• AI summaries now pull from Google Business Profile data, reviews, and website content to generate direct answers about local services
• High-quality, descriptive customer reviews are being surfaced directly in AI-generated local summaries
• Traditional map pack visibility is being supplemented (and sometimes replaced) by narrative AI responses

How to adapt:

• Keep your Google Business Profile meticulously up-to-date with accurate hours, services, and contact information.
• Encourage detailed, helpful reviews that describe specific experiences and outcomes.
• Use local business schema markup to provide clear context about your services and location.
• Create location-specific content that answers common local questions.

For a comprehensive guide on navigating this shift, see our article on Local SEO in an AI-First World.

Proactive AI agents

The next evolution isn’t just conversational search. It’s agentic search, where AI acts on a user’s behalf to complete multi-step tasks autonomously.

Google’s Project Astra, a real-time AI assistant that can understand context through a device’s camera and automate complex tasks, signals this direction clearly. Gartner forecasts that AI agents will augment or automate 50% of all business decisions by 2027.

What this looks like:

• A consumer asks their AI assistant to “plan a weekend in Edinburgh,” and the AI autonomously researches options, books hotels and restaurants, and adds the itinerary to their calendar.
• A procurement manager asks Copilot to “find three suppliers for office furniture under £50k,” and the AI compares vendors, checks reviews, and schedules demos.

Why this matters for SEO:

Optimisation will shift from attracting clicks to ensuring your services and data are discoverable and executable by AI agents. This means:

1. Structured data becomes non-negotiable. AI agents need machine-readable information about pricing, availability, booking processes, and service details.
2. API integrations gain importance. Businesses that can connect their systems to AI platforms will have a direct advantage.
3. Lead quality replaces traffic volume. The metric shifts from “How many visitors?” to “How many qualified actions did AI agents complete?”

The economic model of search is being fundamentally rewritten. Leading analysts forecast a significant decline in traditional search volume, with Gartner predicting a 25% drop by 2026 as users increasingly turn to generative AI assistants.

However, this volume decrease is coupled with a significant increase in the quality and economic value of the traffic that remains. Referral traffic from AI search can have conversion rates up to 23 times higher than traffic from traditional organic search, (source).

This forces a necessary transformation. The successful SEO strategy of 2027 won’t sell traffic generation. It will sell digital authority and measurable business outcomes, requiring deep integration with analytics and CRM systems to prove ROI.

Challenges, ethics, and regulation

The rapid integration of AI into search has outpaced the development of clear legal and ethical frameworks. UK businesses now navigate copyright concerns, data privacy issues, and a dual-track regulatory system comprising both UK and EU legislation.

Google’s quality imperative (E-E-A-T)

In response to the potential for AI to flood the web with low-quality content, Google has doubled down on its core principles. Its official guidance is clear: it rewards high-quality, people-first content that demonstrates Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T).

Crucially, this evaluation is agnostic to the method of production. Google does not penalise content simply because AI was used in its creation. It penalises content that is unhelpful, inaccurate, or created with the primary purpose of manipulating search rankings.

What this means in practice:

• Using automation to generate spammy, low-value content at scale violates Google’s spam policies and is actively targeted by systems like SpamBrain.
• AI should augment human expertise, not replace it.
• Content demonstrating firsthand experience, like a product review from someone who actually used it, carries significant advantage.

Best practices for using AI responsibly:

1. Use AI for initial drafts, research, and summarisation.
2. Apply rigorous human oversight and fact-checking.
3. Add unique value through firsthand experience or original analysis.
4. Ensure content meets E-E-A-T standards regardless of production method.

The debate over AI content detection is largely a red herring. Google’s systems are designed to detect and penalise low-quality, spammy content, not AI-generated content per se. The critical question isn’t “Can Google detect this?” but “Does this content provide real value and meet E-E-A-T standards?”

UK vs. EU AI regulation

As of September 2025, the UK and EU have taken divergent approaches to AI governance, creating a dual compliance challenge for businesses serving both markets.

The UK’s “Pro-Innovation” framework

The United Kingdom has opted against a single, comprehensive AI law, instead pursuing a principles-based regulatory approach outlined in its March 2023 White Paper, (source). This framework is built on five core principles:

• Safety
• Transparency
• Fairness
• Accountability
• Contest-ability

Rather than creating a centralised AI regulator, the government has delegated enforcement to existing bodies:

• Information Commissioner’s Office (ICO) for data protection.
• Ofcom for online safety.
• Competition and Markets Authority (CMA) for fair competition.

This approach is designed to be flexible and adaptable, but creates regulatory ambiguity as businesses must monitor guidance from multiple bodies.

The EU AI act

The European Union has enacted the EU AI Act, a comprehensive, risk-based legislation with significant extraterritorial reach, much like GDPR. The Act categorises AI systems into tiers:

Unacceptable risk: Banned entirely (e.g., government social scoring)

High-risk: Permitted but subject to strict requirements, including conformity assessments and registration in an EU database (e.g., AI used in recruitment or credit scoring)

Limited/Minimal risk: Covers most AI applications relevant to digital marketing with specific transparency obligations

For marketers, key requirements include:

• Chatbots must clearly disclose users are interacting with AI, not humans
• AI-generated “deepfake” content for advertising must be labeled
• Emotion recognition or biometric categorisation for marketing requires explicit notification
• Providers of General-Purpose AI (GPAI) models must disclose copyrighted training material

This creates a dual compliance challenge. While UK businesses operate under a flexible domestic framework, they must adhere to the EU AI Act’s stricter rules when serving individuals within the EU. In practice, the EU AI Act becomes the de facto standard for any UK business with a European customer base.

Copyright and AI content

A primary point of contention is the unauthorised use of publisher content to train Large Language Models. This has led to high-profile lawsuits and a push for greater publisher control.

New technical standards are emerging to provide more granular permissions. Cloudflare’s “Content Signals Policy,” introduced in September 2025, extends the traditional robots.txt protocol, allowing website owners to specify whether content can be used for:

• search: Traditional indexing and snippets
• ai-input: Generating AI answers
• ai-train: Training AI models

This represents a significant step toward giving creators more control over how their intellectual property is used by AI systems.

Protecting your content:

1. Implement updated robots.txt directives using Content Signals or similar policies.
2. Create defensible, original content assets that establish you as a primary source.
3. Monitor how AI platforms are using your content.
4. Consider formal partnerships or licensing agreements with AI providers.

Aspect	United Kingdom	European Union	Action Required
General AI Governance	Principles-based (safety, transparency, fairness), enforced by existing regulators. No single AI law.	Risk-based regulation (EU AI Act) with specific legal requirements based on risk tier.	Conduct risk assessment of all AI tools based on EU AI Act categories if serving EU customers. Monitor guidance from multiple UK regulators.
Chatbot Disclosure	Governed by general transparency principles. Depends on ICO/CMA guidance.	Explicit transparency obligation. Users must be clearly informed they’re interacting with AI.	Implement clear, upfront disclosures on all chatbots stating they are AI-powered.
AI-Generated Content	No specific legal requirement, but guided by transparency principle.	Mandatory disclosure for “deepfakes” or synthetic content that could mislead.	Label AI-generated images or videos used in marketing, especially realistic depictions.
Ad Targeting	Governed by UK GDPR and CMA rules on fair competition.	Governed by GDPR and Digital Markets Act (DMA), which imposes obligations on “gatekeeper” platforms.	Ensure all AI-powered targeting complies with UK GDPR consent and data minimisation principles.
Data Privacy in AI Training	Governed by UK GDPR. Government exploring broad copyright exceptions for text and data mining.	Governed by GDPR. EU AI Act requires GPAI model providers to disclose copyrighted material used for training.	Maintain meticulous records of data used for training in-house AI models. Ensure lawful basis under UK GDPR.

 

A September 2025 report from IAB Europe revealed that while 85% of companies are already using AI for marketing (primarily for ad targeting at 64% and content generation at 61%), governance remains inconsistent. Less than half have specific AI guidelines, and data privacy is cited as the number one concern, (source).

How businesses can adapt: Actionable steps

The shift to AI-powered search isn’t theoretical anymore. It’s happening now, and businesses that adapt quickly will have a significant competitive advantage. Here’s how to get started.

Invest in authority-first content

The new premium is on content AI cannot easily generate. Surface-level articles covering the same topics as everyone else won’t cut it anymore.

Create proprietary knowledge assets:

1. Original research: Conduct surveys, compile industry data, and publish findings that establish you as a primary source
2. Case studies: Document real client results with specific outcomes, challenges, and solutions
3. Expert insights: Share firsthand experience and professional perspectives that only your team can provide
4. Unique data: Develop proprietary metrics, benchmarks, or tools that others reference

This type of content is most likely to be trusted and cited by AI answer engines because it provides information that doesn’t exist anywhere else.

Focus on demonstrating experience:

Remember, AI cannot have genuine real-world experience. Content that demonstrates firsthand knowledge carries significant advantages. Write from direct experience, not just research.

Adopt a dual technical strategy

Google and Microsoft have diverged in their technical priorities. UK businesses need to serve both.

For Google:

• Maintain holistic content quality and semantic relevance.
• Ensure your site is crawlable and provides good page experience.
• Use clear internal linking structures.
• Focus on E-E-A-T principles.

For Bing:

• Implement IndexNow to signal content changes in real time.
• Ensure sitemap <lastmod> dates are always accurate.
• Prioritise freshness signals for time-sensitive content.

For both platforms:

• Deploy comprehensive schema markup (FAQPage, Article, Organisation, Product).
• Structure content with clear headings, lists, and tables for parsability.
• Write concisely with direct answers early in the text.

Optimise for generative experiences

Tailoring content specifically for AI-powered platforms requires a different approach than traditional SEO.

Key strategies:

1. Answer questions directly: Provide clear, concise answers at the start of sections, then elaborate with context.
2. Use conversational language: Write the way people actually speak and search.
3. Build topic clusters: Create comprehensive coverage of a subject area to establish topical authority.
4. Include citations: Link to authoritative external sources to build trust signals.
5. Update regularly: Keep content current so AI models pull the latest information.

Platform-specific considerations:

• Google AI Mode: Optimise for multimodal queries by using high-quality images with descriptive alt text.
• Microsoft Copilot: Create B2B-focused content that professionals would save and share in work environments.
• ChatGPT and other LLMs: Focus on being referenced as an authoritative source through comprehensive, well-cited content.

Partner with specialists

Navigating this fractured landscape requires expertise across traditional SEO, technical implementation, content strategy, and regulatory compliance. The pace of change is accelerating, and staying current demands dedicated resources.

What to look for in an SEO partner:

• Deep understanding of both Google and Microsoft’s AI search ecosystems,
• Experience implementing schema markup and real-time indexing protocols,
• Content strategists who understand E-E-A-T and authority-building,
• Knowledge of UK and EU AI regulatory requirements,
• Analytics capabilities to measure citation frequency and AI visibility, not just rankings,

At Roar, we’ve built our SEO and PPC services specifically for UK businesses navigating this AI-first landscape. We understand the technical divergence between platforms, the regulatory complexity of serving both UK and EU markets, and the content strategies that actually get cited in AI-generated answers.

Ready to future-proof your search visibility? Get in touch with our team to discuss how we can help you adapt.

Final thoughts

SEO isn’t dead. It’s just speaking a different language now.

The businesses winning in 2025 aren’t chasing rankings. They’re building authority AI trusts enough to cite. They’ve implemented the technical foundations that make their expertise visible to machines and valuable to humans.

This shift dismantles decades of established practice, but that’s where the opportunity is. While competitors debate whether AI is a threat or a tool, you can build the infrastructure that makes you indispensable in an answer-first world.

The gap between those who adapt and those who don’t is widening fast. By 2027, it’ll be the difference between being cited and being invisible.

We’ve built our approach around AI-powered search realities, dual-platform optimisation, and authority-first content that gets results.
Speak with our team about where you stand and how to move forward.

FAQs 

How is AI used in SEO?

AI helps in two ways. Tools use it to analyse keywords, predict trends, and automate technical tasks. Search engines use it to generate direct answers instead of just showing links. This means you need to optimise content so AI cites you in its responses, not just rank you in search results.

Will SEO get replaced by AI?

No, but it’s changing. The goal now is becoming the source AI trusts and quotes, not just ranking first. Traditional search traffic is dropping, but the visitors who do click through convert much better. Focus on authority and results, not just traffic numbers.

Is AI good or bad for SEO?

Both. Zero-click searches now make up over 70% of queries, and AI Overviews can cut click-through rates by 70%. But traffic from AI search converts up to 23 times better than regular search. Businesses that create quality, structured content will win. Those that don’t will disappear.

Can ChatGPT do SEO?

ChatGPT can help with tasks like keyword research and content drafts, but it can’t replace people. Google rewards content showing real experience and expertise. AI can’t have genuine experience or provide firsthand insights. Use AI to help with the work, then add the unique value only you can provide.

What AI is best for SEO?

There’s no single best tool. Different AI platforms handle different jobs. Use machine learning tools for keyword research, AI assistants for content structure, and automated crawlers for technical audits. The best AI for SEO is whatever helps your team work smarter while keeping human expertise in charge.

Does SEO have a future?

Yes, but it looks different. By 2028 to 2030, AI-powered search will likely surpass traditional search. Success will mean getting cited by AI, not just ranking high. Businesses investing now in quality content, proper technical setup, and schema markup will dominate. SEO has a future for those who adapt.