Enterprise SEO Statistics UK 2026

Statistics 21–30 — Enterprise AI Adoption, Automation & Data-Driven Operations

Artificial intelligence is already considerably more established inside large businesses than across the wider UK business population.

The UK Business Data Survey 2026 shows that enterprise AI adoption is not limited to experimentation with general-purpose tools.

Large organisations are using AI for research, data analysis, software development and customer-service applications, while many are beginning to integrate AI directly into existing business systems.

That matters for enterprise SEO because the same organisations responsible for search visibility are increasingly using AI inside content, analytics, CRM, software, research and workflow environments.

21. 82% of large UK businesses handling digitised data use AI

That compares with 58% of medium businesses, 51% of small businesses, 41% of micro businesses and 40% of sole traders.

Large organisations therefore show substantially higher AI adoption than every other business-size category measured.

Enterprise SEO implication: AI is already becoming part of the operating environment inside many enterprise organisations, meaning search strategy increasingly needs to coexist with AI-enabled research, content, analytics and workflow systems.

Source: Department for Science, Innovation and Technology, UK Business Data Survey 2026.

22. 56% of large businesses use AI to research information

DSIT explicitly notes that this can include using AI in place of a traditional search engine such as Google.

The equivalent figure was 39% among medium businesses and 36% among small businesses.

Enterprise SEO implication: Search behaviour is changing inside enterprises themselves. Employees are increasingly able to obtain information through AI-generated answers rather than conventional result pages alone.

Source: DSIT, UK Business Data Survey 2026.

23. 32% of large businesses use AI to analyse data or build models

This was more than double the 15% reported by medium businesses and substantially above the 13% reported by small businesses.

Enterprise SEO implication: Organic-search performance can increasingly be incorporated into wider AI-supported modelling, forecasting and business-intelligence environments rather than analysed in isolation.

Source: DSIT, UK Business Data Survey 2026.

24. 21% of large businesses use AI to draft computer code

The equivalent figure was only 8% among medium businesses and 6% among small businesses.

This is particularly relevant to organisations where websites depend on large engineering, development and platform teams.

Enterprise SEO implication: AI-assisted development can accelerate implementation, but it also increases the need for technical SEO requirements to be embedded into engineering standards, testing and deployment governance.

Source: DSIT, UK Business Data Survey 2026.

25. 21% of large businesses use AI for customer-service chatbots

This was three times the 7% reported among medium businesses and more than three times the 6% reported among small businesses.

Customer-service AI can increasingly answer questions that historically might have led users through support pages, FAQs or search engines.

Enterprise SEO implication: Enterprise content increasingly needs to support both external search discovery and internal AI-enabled customer-service systems.

Source: DSIT, UK Business Data Survey 2026.

26. 57% of AI-using large businesses have AI integrated into existing business systems

Examples cited by DSIT include:

• Microsoft Copilot within Microsoft 365.
• AI embedded into CRM systems.
• AI inside finance systems.
• AI functionality within workflow and productivity platforms.

The equivalent integration figure was 31% for both medium and small businesses.

Enterprise SEO implication: AI is moving beyond standalone experimentation towards integration within the enterprise technology stack, increasing the need for search, content and data teams to work with wider organisational systems.

Source: DSIT, UK Business Data Survey 2026.

27. 8% of AI-using large businesses use automated decision-making systems

The figure remains relatively low, suggesting that widespread AI adoption does not necessarily mean that businesses are allowing systems to make significant decisions automatically.

Enterprise implication: Human governance remains important even where enterprise AI use is advanced, particularly where automated systems influence customers, content, products or regulated processes.

Source: DSIT, UK Business Data Survey 2026.

28. 13% of AI-using large businesses use data to train or improve AI systems

This compared with only 2% of sole traders.

The result suggests that some enterprises are beginning to move beyond consuming third-party AI tools towards using their own data in AI-development processes.

Enterprise SEO implication: Proprietary search, content, product, customer and knowledge data may increasingly become inputs into enterprise AI systems, increasing the strategic value of clean and well-governed information architecture.

Source: DSIT, UK Business Data Survey 2026.

29. 56% of AI-using large businesses have a formal written AI policy

This compares with:

• 22% of medium businesses.
• 17% of small businesses.
• 8% of micro businesses.
• 3% of sole traders.

AI governance therefore becomes substantially more formalised at enterprise scale.

Enterprise SEO implication: Enterprise adoption of AI-search, generative content and automated optimisation increasingly needs to operate within formal organisational governance rather than informal experimentation.

Source: DSIT, UK Business Data Survey 2026.

30. 12% of large businesses say data use regularly leads to innovation or new business functions

This was higher than the 5% reported among micro businesses.

The result demonstrates that advanced data use is not solely about measurement or compliance; in some enterprises it contributes directly to organisational innovation.

Enterprise SEO implication: Search data should increasingly be considered a source of market intelligence capable of identifying changing demand, customer language, product opportunities and emerging categories.

Source: DSIT, UK Business Data Survey 2026.

Statistics 31–40 — Enterprise Governance, Data Protection, Infrastructure Risk & Organisational Complexity

Enterprise SEO does not operate independently of governance, infrastructure or regulation.

Large organisations are substantially more likely than smaller businesses to employ specialist compliance staff, train employees, transfer information internationally and depend on external data infrastructure.

These characteristics help explain why enterprise SEO implementation can be slower and more complex even when an organisation has substantial technology and marketing resources.

A seemingly simple search change can involve legal, privacy, engineering, analytics, security, procurement and international stakeholders before it reaches production.

31. 92% of large businesses have someone responsible for leading data-protection compliance

That compares with:

• 74% of medium businesses.
• 64% of small businesses.
• 53% of micro businesses.

Compliance ownership therefore becomes substantially more formalised at enterprise scale.

Enterprise SEO implication: Analytics, tracking, personalisation, consent management and customer-data initiatives increasingly require coordination with formal privacy and governance functions.

Source: Department for Science, Innovation and Technology, UK Business Data Survey 2026.

32. 88% of large businesses employ or outsource specialist staff for data-protection requirements

This compared with 56% of medium businesses, 44% of small businesses and 24% of micro businesses.

Specialist governance is therefore a normal feature of many enterprise organisations.

Enterprise SEO implication: Changes involving cookies, tracking, user data or personalisation increasingly require specialist approval rather than unilateral implementation by marketing teams.

Source: DSIT, UK Business Data Survey 2026.

33. 49% of large businesses ran data-protection training for existing staff

This was substantially higher than:

• 21% of medium businesses.
• 17% of small businesses.
• 10% of micro businesses.

Enterprise implication: Governance requirements are embedded not only through specialist teams but increasingly through formal staff processes.

SEO context: Enterprise search teams working with analytics, experimentation and customer data need to understand organisational compliance requirements as part of implementation.

Source: DSIT, UK Business Data Survey 2026.

34. 35% of large businesses said the burden of data-protection compliance had increased

Large businesses were more likely to report an increase than micro businesses and sole traders.

This may reflect the larger number of data processes, systems, markets and customer interactions requiring oversight at enterprise scale.

Enterprise SEO implication: Search experimentation and measurement increasingly operate in an environment where compliance resources and scrutiny are themselves expanding.

Source: DSIT, UK Business Data Survey 2026.

35. 13% of large businesses had been prevented from using or sharing data because of a legal restriction

This compared with 4% of sole traders.

DSIT notes that this may partly reflect the more sophisticated data-sharing behaviour found among larger businesses.

Enterprise SEO implication: Access to data cannot be assumed simply because the organisation possesses it. Legal restrictions can affect analytics, attribution, customer modelling and cross-system data use.

Source: DSIT, UK Business Data Survey 2026.

36. 73% of large businesses find ICO regulatory guidance clear and easy to understand

This was higher than every smaller business-size category measured.

The figure suggests that although enterprise compliance requirements can be substantial, large organisations also tend to have greater capacity to interpret regulatory guidance.

Enterprise implication: Search governance increasingly benefits from specialist legal and privacy expertise already present within the organisation.

Source: DSIT, UK Business Data Survey 2026.

37. 58% of large businesses storing data off-premises experienced server or cloud downtime

The comparable figures were:

• 28% among medium businesses.
• 31% among small businesses.
• 27% among micro businesses.
• 17% among sole traders.

Enterprise SEO implication: Technical availability is not theoretical. Infrastructure disruption can affect crawling, rendering, analytics, APIs, customer experience and organic performance at significant scale.

Source: DSIT, UK Business Data Survey 2026.

38. 24% of large businesses handling digitised data transfer data internationally

This compared with:

• 18% of medium businesses.
• 10% of micro businesses.
• 9% of sole traders.

International data transfer can support customers, suppliers, technology providers, research, communications and cross-border operations.

Enterprise SEO implication: International SEO frequently sits inside an already cross-border data and technology environment, adding legal, infrastructure and localisation complexity to search operations.

Source: DSIT, UK Business Data Survey 2026.

39. 46% of large businesses transferring data internationally do so for legal or regulatory reasons

The equivalent figure among sole traders was 16%.

International enterprise operations therefore involve regulatory information flows as well as commercial ones.

Enterprise SEO implication: International search programmes frequently operate within regulatory structures extending beyond marketing, including reporting, governance and cross-border data-management requirements.

Source: DSIT, UK Business Data Survey 2026.

40. Large businesses transferring data internationally reported a median of six countries

Businesses were allowed to list up to ten countries, so some organisations may transfer data across an even wider geographic footprint.

The measure demonstrates the multi-country operating complexity common within enterprise organisations.

Enterprise SEO implication: Enterprise search programmes often need to coordinate websites, languages, markets, governance and technology across multiple jurisdictions rather than optimising one national website independently.

Source: DSIT, UK Business Data Survey 2026.

Statistics 41–50 — Google Search, AI Search & Enterprise Discovery

The final ten statistics move from the internal enterprise environment to the external search landscape in which large organisations compete for visibility.

Google remains the UK’s dominant search service, but the structure of discovery is changing.

AI Overviews are increasingly appearing inside conventional search, standalone generative-AI services have developed substantial audiences, and conversational search allows users to express more detailed requirements than conventional keyword queries.

For enterprises managing complex brands, products, services, sectors and international markets, this expands the search challenge from ranking pages towards ensuring the organisation is correctly understood and represented across both traditional and generated discovery systems.

41. 96% of UK online adults use search engines

Search engines therefore remain one of the most widespread digital gateways to information.

For enterprises, search demand can include:

• Brands.
• Products.
• Services.
• Locations.
• Careers.
• Investor information.
• Support.
• Research.
• Corporate information.

Enterprise SEO implication: Search continues to influence far more than customer acquisition. It can shape how multiple stakeholder groups discover and understand a large organisation.

Source: Ofcom, Adults’ Media Use and Attitudes 2026.

42. Google Search reaches 82% of UK adults

Ofcom describes Google as by far the most widely used search service in the UK.

This gives Google continued strategic importance even as other discovery platforms expand.

Enterprise SEO implication: Enterprise search strategies still need strong Google visibility while preparing for a broader AI-assisted discovery environment.

Source: Ofcom, From Apps to AI Search: How the UK Goes Online in 2025.

43. Around 3 billion Google searches take place in the UK every month

Those searches span commercial, informational, navigational, professional and personal needs.

Enterprise organisations can appear across thousands of different intent types rather than competing only for a narrow set of commercial keywords.

Enterprise SEO implication: Enterprise search architecture should map the organisation’s wider demand universe, not simply a shortlist of high-volume keywords.

Source: Ofcom, From Apps to AI Search.

44. UK adults generated nearly 9 billion Google Search page views in October 2025

Page views are not equivalent to individual search queries and should not be directly compared with the three-billion-search figure.

The measure nevertheless demonstrates the enormous volume of interaction occurring within Google’s search interface.

Enterprise SEO implication: Large organisations compete within a search environment receiving billions of monthly user interactions before AI assistants and other discovery platforms are considered.

Source: Ofcom, Adults’ Media Use and Attitudes 2026, citing Ipsos iris.

45. Around 30% of Google searches now show AI Overviews

Generated answers are therefore becoming part of mainstream search rather than a separate experimental product.

For enterprise organisations, this introduces another layer between the user’s question and conventional organic results.

Enterprise SEO implication: Enterprise visibility increasingly depends on whether search systems can correctly interpret an organisation’s entities, expertise, products, services and supporting sources.

Source: Ofcom, From Apps to AI Search.

46. 53% of UK adults often see AI-generated search summaries

In many cases, users are not actively selecting an AI service; generated summaries are being inserted into the conventional search experience they already use.

Enterprise SEO implication: AI-search visibility can influence enterprise discovery even among users who have not deliberately adopted a standalone conversational assistant.

Source: Ofcom, From Apps to AI Search.

47. ChatGPT received 1.8 billion UK visits in the first eight months of 2025

Not every visit represents search or commercial discovery.

However, the audience scale means generative AI has become a meaningful information environment alongside conventional search.

Enterprise SEO implication: Large organisations increasingly need to consider how their brand, products, leadership, expertise and research may be represented within conversational systems.

Source: Ofcom, From Apps to AI Search and Online Nation 2025.

48. ChatGPT’s measured UK traffic increased almost fivefold year on year

That represents approximately 4.9 times as many visits.

CGO Media calculation: 1.8 billion divided by 368 million equals approximately 4.9.

Enterprise implication: Large organisations may need to adapt faster than traditional annual SEO planning cycles when discovery platforms themselves can achieve rapid audience growth.

Source: Ofcom. Calculation by CGO Media.

49. 59% of UK adults recently used generative AI

Usage reached at least 75% among adults below the age of 45.

Among generative-AI users in DSIT’s online sample, 75% used these tools at least weekly and 35% reported daily or more frequent use.

Enterprise SEO implication: AI-assisted information discovery is becoming an increasingly normal behaviour among the audiences enterprises need to reach, particularly younger professional and consumer groups.

Source: Department for Science, Innovation and Technology, Public Engagement Survey 2025/2026.

50. AI Mode queries can be two to three times longer than traditional searches

AI Mode is designed for more complex, multi-part questions and can issue multiple underlying searches to explore different aspects of a user’s request.

For enterprises, that changes the shape of discoverable demand.

A conventional enterprise search might be:

“Enterprise cybersecurity platform”

A conversational search could instead ask:

“Which enterprise cybersecurity platforms are suitable for a regulated UK financial-services organisation with operations across Europe, more than 5,000 employees and existing Microsoft infrastructure?”

Enterprise SEO implication: Entity clarity, sector expertise, use cases, integrations, geographic coverage, evidence and authority become more important as users express increasingly detailed requirements.

Source: Google UK, Introducing AI Mode in the UK.

CGO Media Analysis — What the 50 Enterprise SEO Statistics Tell Us

Taken together, the 50 statistics show that enterprise SEO is fundamentally different from small-business or mid-market search optimisation.

Large businesses represent only a tiny proportion of the UK business population, yet they account for a substantial share of employment and turnover and operate some of the country’s most complex digital infrastructures.

At the same time, these organisations are adopting cloud services, artificial intelligence, automated systems and data-driven processes at significantly higher rates than smaller businesses.

The result is an enterprise search environment where success depends not only on SEO expertise but on organisational coordination, technology, governance, data quality and the ability to adapt to changing search and AI interfaces.

1. Enterprise SEO Operates Across a Small Number of Economically Powerful Organisations

Only 0.15% of UK private-sector businesses have 250 or more employees.

Yet those businesses account for 40% of private-sector employment and almost half of measured turnover.

This creates a distinctive search environment.

Enterprise SEO may involve relatively few organisations, but those organisations often operate:

• Multiple brands.
• Large product or service portfolios.
• International websites.
• Thousands or millions of URLs.
• Large customer databases.
• Multiple technology systems.

2. Website Ownership Is No Longer Meaningful Differentiation

With 99% of large businesses already operating websites, simply being online creates effectively no competitive advantage.

The differentiators increasingly become:

• Technical efficiency.
• Information architecture.
• Content governance.
• Authority.
• Data quality.
• International consistency.
• Search accessibility.

For enterprise organisations, website presence is the baseline.

Performance depends on how effectively the digital estate is managed.

3. Enterprise SEO Is Increasingly an Infrastructure Discipline

Large businesses are more likely to use public cloud services, external data centres, APIs, multiple analytics systems and integrated technology platforms.

That means technical SEO problems can originate far below the CMS layer.

Issues may be caused by:

• Rendering architecture.
• CDNs.
• APIs.
• Deployment systems.
• Authentication.
• Cloud infrastructure.
• International routing.

4. Data Is Becoming Part of Enterprise Search Strategy

Nearly seven in ten large businesses analyse data to generate new insights.

This creates an opportunity for enterprise SEO to become more closely connected with:

• Business intelligence.
• Customer demand.
• Product performance.
• Market research.
• Revenue forecasting.
• Customer behaviour.

Search data can reveal what customers are asking for before those questions appear in conventional market reports.

Enterprise SEO therefore has the potential to become a source of organisational intelligence rather than merely an acquisition channel.

5. AI Is Already Inside the Enterprise Operating Model

More than four in five large businesses handling digitised data already use AI for at least one purpose.

This is important because AI is not simply an external search platform enterprises need to optimise for.

It is increasingly being used internally for:

• Research.
• Data analysis.
• Code generation.
• Customer service.
• Automation.

Enterprise SEO teams therefore need to think about both sides of AI:

AI Inside the Organisation

and

AI Used by Customers to Discover the Organisation

6. Governance Is Part of Search Performance

Large organisations have formal privacy leadership, specialist compliance teams, AI policies and international data responsibilities.

These controls are necessary, but they also affect how quickly digital changes can be implemented.

Enterprise SEO therefore often depends on:

• Clear ownership.
• Defined workflows.
• Prioritisation frameworks.
• Pre-approved technical standards.
• Cross-functional governance.

7. International Complexity Compounds Search Complexity

Large businesses are more likely to transfer data internationally and operate across multiple jurisdictions.

The same complexity frequently applies to enterprise websites.

International search programmes may need to coordinate:

• Different domains or subdirectories.
• Multiple languages.
• Regional products.
• Local regulations.
• Different currencies.
• Market-specific content.
• International teams.

Enterprise SEO therefore needs global standards without eliminating necessary local variation.

8. Search Visibility Increasingly Depends on Entity Clarity

AI-generated search introduces an additional requirement beyond ranking individual pages.

Search and AI systems increasingly need to understand:

• Who the organisation is.
• What it does.
• Which products and services it provides.
• Where it operates.
• Which sectors it serves.
• What expertise it possesses.

For enterprises with multiple brands, subsidiaries and business units, inconsistent information can make this especially difficult.

9. AI Search Makes Enterprise Authority More Important

As users ask longer and more complex questions, enterprises may increasingly be evaluated against multiple criteria within the same request.

A buyer may ask for a provider with a particular:

• Industry specialism.
• Geographic footprint.
• Technology integration.
• Security certification.
• Company size.
• Research capability.
• Regulatory experience.

This increases the importance of explicit evidence.

General statements such as “market-leading provider” become less useful than clear documentation showing what the organisation actually does and why it qualifies for consideration.

10. Enterprise SEO Is Becoming an Organisational System

The strongest conclusion from the 50 statistics is that enterprise SEO should not be treated as a collection of isolated optimisation tasks.

It increasingly functions as a system connecting:

• Technology.
• Content.
• Data.
• Brand.
• Legal.
• Analytics.
• International teams.
• Artificial intelligence.

The enterprise organisations most capable of sustaining search visibility are therefore likely to be those that make search requirements repeatable across the organisation.

What UK Enterprises Should Do in 2026

The 50 statistics show that enterprise SEO now operates across technology, governance, data, content, AI and organisational processes.

For large organisations, the strongest strategy is therefore not to create a longer list of SEO tasks.

It is to build an operating system that allows search requirements to be implemented consistently across large websites, multiple teams and changing discovery environments.

1. Establish Clear Enterprise SEO Ownership

Large organisations often lose search performance because responsibility is distributed across too many teams.

A mature enterprise programme should define:

• Who owns organic search strategy.
• Who owns technical implementation.
• Who controls templates and CMS functionality.
• Who approves content.
• Who manages analytics and measurement.
• Who signs off legal, privacy and compliance issues.

Without clear ownership, technically correct recommendations can remain unimplemented for months.

2. Build SEO Requirements Into Engineering Standards

Enterprise websites frequently depend on cloud platforms, APIs, JavaScript frameworks, deployment pipelines and multiple development teams.

SEO requirements should therefore be embedded into:

• Development standards.
• Component libraries.
• Template specifications.
• QA processes.
• Release checklists.
• Automated testing.

This reduces the need to rediscover and repair the same technical problems repeatedly.

3. Create a Scalable Technical SEO Monitoring System

Large websites should not rely only on occasional manual audits.

Continuous monitoring should cover:

• Indexation.
• Crawl behaviour.
• Canonicalisation.
• Robots directives.
• Sitemaps.
• Status codes.
• Rendering.
• Internal linking.
• Structured data.
• Page performance.

Priority should be based on commercial impact rather than raw error counts.

4. Build a Governed Enterprise Information Architecture

Enterprise information architecture needs to make large organisations understandable to both users and machines.

That includes clear relationships between:

• Corporate entities.
• Brands.
• Products.
• Services.
• Industries.
• Locations.
• Research.
• Leadership.

Duplicate or contradictory representations of the same entity should be reduced wherever possible.

5. Standardise Content Governance

Large organisations cannot rely on each business unit inventing its own content structure.

Enterprises should define standards for:

• Page purpose.
• Search intent.
• Headings.
• Internal links.
• Expert attribution.
• Claims and evidence.
• Metadata.
• Structured data.
• Review cycles.

Standardisation reduces inconsistency while still allowing local and sector-specific variation.

6. Connect Search Data With Business Intelligence

Large businesses already use data extensively to generate insights.

Search data should therefore be connected with:

• Revenue.
• CRM data.
• Product demand.
• Market trends.
• Customer journeys.
• Lead quality.
• Regional performance.

The objective is to move beyond reporting traffic and rankings towards understanding commercial demand.

7. Build Stronger Entity and Brand Signals

AI-assisted search increases the importance of clearly defining the organisation and its relationships.

Enterprises should ensure consistency around:

• Corporate name.
• Brands and subsidiaries.
• Locations.
• Products and services.
• Leadership.
• Sector expertise.
• Research and intellectual property.

Independent corroboration through reputable third-party sources also becomes increasingly important.

8. Publish Evidence Worth Citing

Enterprise organisations often possess data and expertise that smaller competitors cannot easily replicate.

That should be turned into citable assets such as:

• Original research.
• Benchmark reports.
• Datasets.
• Technical papers.
• Industry statistics.
• Methodologies.
• Expert commentary.

These assets can support traditional SEO, digital PR and AI citation visibility simultaneously.

9. Prepare for AI Search Without Creating a Separate Content Universe

Enterprise organisations do not need to duplicate their websites for AI search.

They should strengthen the underlying information systems that both search engines and AI systems can use.

That includes:

• Clear entity relationships.
• Authoritative content.
• Explicit expertise.
• Consistent facts.
• Structured information.
• Strong independent references.

AI-search readiness should be built on top of strong enterprise SEO rather than treated as an isolated initiative.

10. Create an Enterprise AI Governance Layer

With more than half of AI-using large businesses already operating formal AI policies, search teams should align with wider organisational governance.

Policies should address:

• AI-generated content.
• Human review.
• Source verification.
• Confidential data.
• Brand accuracy.
• Automated publication.

The objective is to gain efficiency without allowing low-quality or inaccurate content to scale across a large website.

11. Build International SEO Standards Centrally

Global organisations need common rules for:

• Domains and subdirectories.
• Hreflang.
• Canonicals.
• Localisation.
• Translation.
• Regional products.
• Market-specific content.

These standards should be governed centrally while allowing markets to adapt where genuine local differences exist.

12. Prioritise by Commercial Impact

Enterprise SEO backlogs can contain thousands of issues.

Not all deserve equal attention.

Prioritisation should consider:

• Revenue affected.
• Search demand.
• Number of URLs impacted.
• Strategic importance.
• Implementation effort.
• Risk.
• Speed to value.

This helps enterprise teams avoid spending months fixing technically interesting problems with limited commercial significance.

Enterprise SEO Trends UK 2026–2027

The 50 statistics in this report point towards several clear directions for enterprise SEO over the next 12 to 24 months.

These are not guaranteed outcomes.

They are evidence-led trends based on large-business digital adoption, AI usage, enterprise governance, cloud infrastructure, search behaviour and the rapid expansion of AI-assisted discovery.

1. Enterprise SEO Will Become More Embedded in Engineering

Large organisations already depend heavily on cloud infrastructure, data centres, APIs and integrated business systems.

As websites become more technically complex, search performance will increasingly depend on decisions made by engineering teams.

SEO requirements are therefore likely to become more tightly integrated into:

• Component libraries.
• Design systems.
• Development standards.
• Automated testing.
• Deployment pipelines.
• Platform migrations.

2. Search Governance Will Become More Formalised

Enterprise organisations already show high levels of formal privacy and AI governance.

SEO is likely to follow the same direction.

Large organisations increasingly need documented rules covering:

• Indexation.
• Canonicalisation.
• Internal linking.
• Content standards.
• International SEO.
• Structured data.
• AI-generated content.
• Site migrations.

This reduces reliance on individual specialists remembering every requirement manually.

3. Enterprise AI Adoption Will Accelerate Search Automation

With 82% of large businesses handling digitised data already using AI, search teams are likely to increase AI-assisted workflows.

These may include:

• Technical issue detection.
• Keyword classification.
• Internal-link recommendations.
• Content analysis.
• Schema generation.
• Reporting.
• Competitive research.

The main challenge will increasingly be quality control rather than access to AI itself.

4. Search Data Will Move Further Into Business Intelligence

Large businesses already analyse data at much higher rates than smaller organisations.

Search data is therefore likely to become more closely integrated with:

• CRM systems.
• Revenue data.
• Product demand.
• Customer research.
• Market forecasting.
• Regional performance.

This will increase pressure on SEO teams to explain commercial impact rather than report traffic in isolation.

5. Entity Architecture Will Become More Important

AI-assisted discovery increases the importance of how clearly an organisation is represented as an entity.

Large businesses often create complexity through:

• Multiple brands.
• Subsidiaries.
• Acquisitions.
• Regional entities.
• Product families.
• Different naming conventions.

Enterprises are therefore likely to invest more heavily in consistent entity architecture and knowledge relationships.

6. Source Authority Will Become a More Visible Enterprise KPI

Traditional SEO has historically focused heavily on rankings and backlinks.

AI-assisted discovery introduces another question:

Is the organisation being used as a source?

Enterprises with original research, technical documentation, industry data and expert commentary may increasingly measure:

• AI citations.
• Source mentions.
• Research references.
• Brand inclusion in generated answers.

These measures are still evolving, but they are likely to become more relevant alongside traditional search KPIs.

7. Enterprise Content Will Need Stronger Evidence

Generic corporate content is likely to become less competitive as both search engines and AI systems gain access to increasing volumes of similar information.

Enterprise content will increasingly need:

• Original data.
• Named experts.
• Documented methodology.
• Case studies.
• Technical evidence.
• Independent corroboration.

This may shift enterprise content strategies away from volume and towards evidential authority.

8. International SEO Will Become More Centralised Technically

Large businesses commonly operate across multiple jurisdictions and transfer data internationally.

This creates strong incentives to standardise the technical foundations of international SEO centrally.

Enterprises are likely to increasingly centralise:

• Hreflang logic.
• Canonical rules.
• URL standards.
• Translation workflows.
• Structured data.
• Measurement.

Markets can then localise content without rebuilding the technical framework independently.

9. AI Search Will Expand Enterprise Long-Tail Demand

Conversational search allows users to describe more complex business requirements.

This may create demand that was previously difficult to represent through conventional keyword tools.

Enterprise visibility may increasingly depend on how clearly organisations document:

• Industry expertise.
• Technology integrations.
• Geographic coverage.
• Compliance capabilities.
• Organisation scale.
• Specific use cases.

10. AI Search and Traditional SEO Will Converge

The distinction between “SEO” and “AI SEO” is likely to become less useful over time.

Both increasingly depend on many of the same foundations:

• Technical accessibility.
• Clear entities.
• Authoritative content.
• Structured information.
• Strong source signals.
• Consistent brand information.

Enterprises will increasingly build one search architecture designed to support multiple discovery environments.

11. Enterprise SEO Measurement Will Broaden

Rankings will remain useful, but enterprise teams are likely to use a wider measurement framework.

This may include:

• Organic revenue.
• Qualified pipeline.
• Brand search.
• Share of search.
• AI referrals.
• AI citations.
• Entity coverage.
• Research visibility.
• Regional performance.

The objective will increasingly be to measure enterprise discovery rather than only conventional organic traffic.

12. Implementation Speed Will Become a Competitive Advantage

Enterprise organisations often know what needs to be changed long before they actually implement it.

The organisations that reduce time between:

Detection → Decision → Development → Deployment

may gain an important search advantage.

This is particularly relevant as search interfaces and AI systems evolve faster than traditional enterprise planning cycles.

Research Methodology & Limitations

This report was prepared by the CGO Media Research Team to provide an evidence-based view of the environment in which enterprise SEO operates in the UK in 2026.

The report combines official business-population statistics, large-business digital-adoption data, regulatory and governance evidence, audience measurement, search behaviour and first-party platform information.

It does not claim that all 50 statistics directly measure enterprise SEO performance.

Instead, the statistics describe the organisational, technological and discovery environment within which enterprise SEO operates.

Research Scope

The 50 statistics were organised into five evidence groups:

1. UK Enterprise Business Population & Economic Scale — large-business numbers, employment, turnover and sector concentration.
2. Enterprise Websites, Data & Digital Infrastructure — website ownership, digitised data, tracking, cloud and infrastructure.
3. Enterprise AI Adoption & Automation — AI use, research, data analysis, code generation, chatbots, integration and governance.
4. Enterprise Governance & Infrastructure Risk — data protection, compliance, outages, international data transfers and organisational complexity.
5. Google Search, AI Search & Enterprise Discovery — search usage, AI Overviews, ChatGPT, generative AI and conversational search.

Primary Source Standard

CGO Media prioritised original, official or first-party sources wherever possible.

The principal sources include:

• Department for Business and Trade.
• Department for Science, Innovation and Technology.
• Ofcom.
• Ipsos iris.
• Google.

Generic SEO-statistics round-ups, unsourced claims and secondary marketing articles were not treated as primary evidence when a stronger original source was available.

Definition of a Large Business

The Department for Business and Trade defines a large business as an organisation with 250 or more employees.

That definition is used throughout the business-population section.

The UK Business Data Survey also uses a 250+ employee category for large businesses, allowing reasonably consistent comparison across the enterprise-specific sections.

Business Population Estimates

Statistics 1–10 use the Department for Business and Trade Business Population Estimates.

These estimates cover the UK private-sector business population and include both registered and unregistered businesses where relevant.

They provide estimates for:

• Business numbers.
• Employment.
• Turnover.
• Business size.
• Industry sector.

Turnover figures exclude Financial and Insurance Activities where comparable turnover data is unavailable.

Turnover Does Not Equal Profit

The £2.696 trillion enterprise turnover figure measures business turnover rather than profit, market capitalisation or economic value added.

It should therefore not be interpreted as enterprise profit or enterprise SEO opportunity.

The figure is used to demonstrate the commercial scale of large businesses within the measured private-sector economy.

Enterprise Website Ownership

The 99% website-ownership statistic establishes that websites are effectively universal among large businesses.

It does not measure:

• Website quality.
• SEO maturity.
• Organic visibility.
• Traffic.
• Conversion.
• Technical performance.

Website ownership is therefore treated as evidence of digital presence rather than evidence of successful enterprise SEO.

Digitised Data Measures

The UK Business Data Survey contains several different data-related populations.

Some questions apply to all businesses, while others apply only to businesses handling:

• Digitised data.
• Personal data.
• Non-personal data.
• AI systems.
• Off-premises data storage.

The denominator therefore changes between statistics.

This is why the report identifies the relevant survey population where necessary rather than treating every percentage as directly comparable.

Cloud and Infrastructure Statistics

Statistics on public-cloud providers, external data centres and downtime describe elements of enterprise technology infrastructure.

They do not prove that a specific enterprise website is hosted in a particular environment or that cloud adoption automatically improves or harms SEO.

These figures are used to illustrate the infrastructure complexity within which enterprise websites increasingly operate.

AI Adoption Measures

The 82% AI-adoption figure refers to large businesses handling digitised data that reported using AI for at least one purpose.

It should not be interpreted as meaning 82% of every UK large business uses every form of AI.

Similarly, individual use cases such as:

• Research.
• Data analysis.
• Code generation.
• Chatbots.

measure specific reported applications rather than overall AI maturity.

AI Integration vs AI Experimentation

The statistic showing 57% integration of AI into existing systems applies to large businesses already using AI.

This is different from the wider 82% AI-adoption figure.

The two statistics should not be combined without preserving their different denominators.

Formal AI Policies

The 56% formal AI-policy statistic also applies to AI-using large businesses.

It measures reported existence of a written policy, not:

• Policy quality.
• Policy enforcement.
• Compliance effectiveness.
• AI safety maturity.

The statistic is therefore used as evidence of increasing governance formalisation rather than proof of governance effectiveness.

Data-Protection and Governance Statistics

Many governance statistics apply specifically to businesses handling digitised personal data or employing staff.

These include:

• Data-protection leadership.
• Specialist compliance staff.
• Training.
• Compliance burden.
• Legal restrictions on data use.

The report uses these figures to describe organisational complexity, not as direct measures of SEO performance.

Infrastructure Downtime

The 58% downtime statistic applies to large businesses storing or processing data away from their premises.

It does not mean 58% of all large-business websites were unavailable.

Downtime can affect many types of infrastructure and services.

The figure is used to demonstrate the operational dependency large businesses can have on external infrastructure.

International Data Transfers

International data-transfer statistics measure the movement of business data between countries.

They do not directly measure:

• International SEO.
• International website ownership.
• Number of markets served.
• Languages supported.

They are included because they provide evidence of the cross-border organisational complexity often found in enterprise environments.

Search Usage vs Enterprise Search

Statistics 41–50 primarily describe the wider UK search environment.

They are not enterprise-user-only measurements.

For example, Google Search reach and monthly search volume include:

• Consumers.
• Employees.
• Journalists.
• Researchers.
• Investors.
• Business buyers.

These figures are included because large organisations need to be discoverable by multiple stakeholder groups within the same search ecosystem.

Searches, Page Views and Visits Are Different Measures

The report maintains a clear distinction between:

• Search queries.
• Page views.
• Visits.
• Audience reach.
• Reported usage.

For example, nearly nine billion Google Search page views should not be interpreted as nine billion unique searches.

Similarly, ChatGPT visits should not be treated as prompts or search queries.

AI Overviews

The estimate that around 30% of Google searches show AI Overviews demonstrates the prevalence of AI-generated search interfaces.

It does not establish:

• Click-through impact.
• Enterprise citation rates.
• Conversion impact.
• Brand-recommendation impact.
• Revenue impact.

Those outcomes require separate research.

Generative-AI Adoption

The 59% UK adult generative-AI adoption figure measures broad AI use across many purposes.

It does not mean 59% of adults use AI for enterprise purchasing, supplier discovery or corporate research.

The figure is used to establish the growing familiarity of UK audiences with conversational AI interfaces.

ChatGPT Traffic

ChatGPT traffic statistics represent visits to the platform.

They do not identify:

• The number of prompts.
• The number of enterprise-related queries.
• The number of brand recommendations.
• The number of purchases influenced.

The figures therefore measure platform scale rather than enterprise search performance.

Google AI Mode Data

Google’s statement that early AI Mode queries can be two to three times longer than traditional searches is first-party platform evidence.

It is useful for understanding the potential change in query structure.

However, it should not automatically be generalised to:

• All Google users.
• All enterprise buyers.
• All countries.
• All AI platforms.

CGO Media Calculations

Where CGO Media performs calculations using published data, the result is explicitly identified as a CGO Media calculation.

For example, the report calculates the approximate 4.9× growth in measured ChatGPT UK visits using Ofcom-reported figures.

The underlying values remain attributable to the original publisher.

Source Evidence vs CGO Media Interpretation

Labels such as:

• Enterprise SEO implication
• Enterprise implication
• CGO Media interpretation
• 2026–2027 direction

represent CGO Media analysis rather than conclusions published by DBT, DSIT, Ofcom, Ipsos or Google.

Correlation and Causation

The simultaneous growth of enterprise AI adoption and AI-assisted search does not prove that one caused the other.

Similarly, cloud adoption, data analysis or formal governance do not automatically cause stronger SEO performance.

Causal conclusions require research specifically designed to test those relationships.

Research Limitations

This report should be interpreted with the following limitations in mind:

• Different datasets cover different time periods.
• Survey denominators vary between questions.
• Some evidence is self-reported.
• Large-business classification is based on employee count rather than website complexity.
• Website ownership does not measure SEO maturity.
• Cloud use does not measure technical SEO quality.
• AI use does not measure AI-search readiness.
• AI policies do not measure policy effectiveness.
• Data-transfer figures do not directly measure international SEO.
• Search reach does not equal enterprise buying intent.
• Page views do not equal search queries.
• ChatGPT visits do not equal enterprise search queries.
• AI Overview exposure does not establish traffic or revenue impact.
• Enterprise performance varies substantially by industry and business model.
• 2026–2027 trend sections are evidence-led interpretation rather than guaranteed forecasts.

Frequently Asked Questions — Enterprise SEO Statistics UK 2026

The questions below address the main issues raised by the 50 statistics, including the scale of UK enterprise businesses, website adoption, digital infrastructure, artificial intelligence, governance, Google Search and AI-assisted discovery.

1. How many large businesses are there in the UK?

At the start of 2025, there were approximately 8,335 UK private-sector businesses with 250 or more employees.

That is the standard large-business definition used by the Department for Business and Trade.

2. What percentage of UK businesses are large enterprises?

Large businesses represent only 0.15% of the UK private-sector business population.

Despite their small number, they account for a disproportionately large share of employment and turnover.

3. How economically important are large UK businesses?

Large businesses employ approximately 11.25 million people, representing around 40% of private-sector employment.

They also generate approximately £2.696 trillion in measured turnover, equal to about 49% of measured private-sector turnover.

4. What percentage of large UK businesses have a website?

The UK Business Data Survey 2026 found that 99% of large businesses have a website.

Website ownership is therefore effectively universal at enterprise scale.

5. Does having a website mean an enterprise has mature SEO?

No.

Website ownership says nothing about:

• Technical SEO quality.
• Search visibility.
• Information architecture.
• Content governance.
• International SEO.
• Entity clarity.
• AI-search readiness.

At enterprise scale, the challenge is not having a website but managing a large digital estate effectively.

6. How widely is AI used by large UK businesses?

Among large businesses handling digitised data, 82% reported using AI for at least one purpose.

Common applications include research, data analysis, code generation and customer-service chatbots.

7. How are enterprises using AI for research?

56% of large businesses handling digitised data reported using AI to research information.

DSIT notes that this can include using AI in place of conventional search engines for some tasks.

This is important because AI is changing information discovery inside organisations as well as outside them.

8. Do large businesses have formal AI governance?

Among AI-using large businesses, 56% reported having a formal written AI policy.

That is substantially higher than among smaller businesses.

Formal governance is therefore becoming a normal component of enterprise AI adoption.

9. How important is data governance in enterprise SEO?

Very important.

92% of large businesses in the relevant survey population have someone responsible for leading data-protection compliance, while 88% employ or outsource specialist compliance staff.

This affects how enterprise teams use:

• Analytics.
• Cookies.
• Tracking.
• Personalisation.
• Customer data.
• AI systems.

10. Why is technical SEO more complex for enterprises?

Large businesses frequently operate cloud platforms, APIs, external data centres, multiple websites and integrated technology systems.

Technical problems can therefore originate in:

• Hosting.
• Rendering.
• CDNs.
• APIs.
• Deployment pipelines.
• CMS architecture.
• Authentication.

This means technical SEO often requires collaboration with engineering rather than being solved entirely within marketing.

11. Is Google still important for enterprise SEO?

Yes.

Search-engine use remains near-universal among UK online adults, while Google continues to reach the majority of the connected population.

Enterprise search demand can include:

• Products.
• Services.
• Brands.
• Research.
• Careers.
• Locations.
• Support.
• Investor information.

12. Is AI search replacing enterprise SEO?

The available evidence does not support that conclusion.

AI-generated summaries are increasingly appearing inside Google Search, while standalone assistants such as ChatGPT are developing large audiences.

Traditional SEO foundations remain essential because both conventional search and AI systems depend on accessible, structured and authoritative information.

13. What percentage of Google searches show AI Overviews?

Ofcom reports that approximately 30% of Google searches now display AI-generated Overviews.

Generated answers are therefore becoming part of the mainstream search environment.

14. How popular is ChatGPT in the UK?

Ofcom measured approximately 1.8 billion UK visits to ChatGPT between January and August 2025.

That was up from 368 million in the equivalent period of 2024.

The figure measures visits rather than search queries or enterprise purchasing activity.

15. Why does entity authority matter for enterprise SEO?

Large organisations often contain multiple brands, subsidiaries, products, locations and business units.

Search engines and AI systems need to understand the relationships between them.

Clear entity architecture helps systems determine:

• Who the organisation is.
• What it does.
• Where it operates.
• Which sectors it serves.
• Which products and services belong to it.

16. What should enterprises prioritise for SEO in 2026?

A sensible sequence is:

1. Define search ownership and governance.
2. Fix major technical and infrastructure barriers.
3. Embed SEO requirements into engineering standards.
4. Standardise information architecture and content governance.
5. Connect search data with commercial and business-intelligence systems.
6. Strengthen entity and brand clarity.
7. Publish authoritative and citable research or evidence.
8. Build international SEO standards.
9. Prepare for AI-assisted discovery.
10. Measure revenue, demand and business impact rather than rankings alone.

Conclusion — Enterprise SEO Statistics UK 2026

The 50 statistics in this report show that enterprise SEO now operates across far more than rankings, keywords and individual webpages.

Large businesses represent only a tiny fraction of the UK business population, yet they account for a major share of employment and turnover and operate some of the country’s most complex digital estates.

At the same time, these organisations are highly data-driven, heavily cloud-dependent, increasingly AI-enabled and subject to formal governance, legal and international requirements.

The result is a search environment where performance depends on whether technology, content, data, authority and governance can work together at scale.

Enterprise Scale Changes the Nature of SEO

Only 0.15% of UK private-sector businesses employ 250 or more people.

Yet those organisations account for 40% of private-sector employment and 49% of measured turnover.

That concentration means enterprise search visibility can have consequences across businesses with exceptionally large customer bases, workforces, brands and commercial footprints.

The Website Is Only One Layer of the Enterprise System

With website ownership effectively universal among large businesses, the competitive difference lies in what sits behind the website.

That can include:

• Cloud infrastructure.
• APIs.
• Data platforms.
• Analytics.
• Multiple CMS environments.
• International systems.
• Engineering pipelines.

Technical SEO therefore increasingly depends on infrastructure and engineering decisions that may sit far outside the marketing team.

AI Is Already Embedded Inside Large Organisations

The enterprise AI statistics show that large businesses are not merely experimenting with AI.

Many already use it for:

• Research.
• Data analysis.
• Code generation.
• Customer service.
• Integrated business systems.

This creates a two-sided search challenge.

Enterprises need to understand how AI is used internally while also adapting to the way customers and stakeholders increasingly use AI externally to discover information.

Governance Is Now Part of Search Performance

Large organisations operate within formal legal, privacy, compliance and AI-governance frameworks.

Search teams therefore cannot treat implementation as a purely technical matter.

Enterprise SEO increasingly requires:

• Clear ownership.
• Defined responsibilities.
• Documented standards.
• Approval processes.
• Cross-functional collaboration.

A good SEO recommendation has limited value if the organisation cannot implement it reliably.

Google Search Remains Fundamental

Search-engine use remains near-universal among UK online adults, and Google continues to dominate conventional search.

For enterprises, Google can influence far more than sales.

It can affect discovery across:

• Brand.
• Products.
• Services.
• Research.
• Careers.
• Support.
• Locations.
• Investor information.

Traditional SEO therefore remains strategically important even as AI-assisted discovery grows.

AI Search Expands the Enterprise Discovery Challenge

AI Overviews and conversational assistants create new routes through which organisations can be evaluated before a user visits the corporate website.

Longer and more detailed questions place increasing value on:

• Entity clarity.
• Sector expertise.
• Geographic coverage.
• Technical capabilities.
• Evidence.
• Source authority.

The search objective therefore expands from ranking a page towards being accurately represented within a generated answer or recommendation.

Research Usage, Citation & Press

This research has been prepared by the CGO Media Research Team as part of CGO Media’s wider programme examining SEO, AI search, GEO, digital authority and changing search behaviour in the UK.

Journalists, researchers, businesses, universities, analysts and other organisations may reference individual statistics, findings and CGO Media analysis from this report provided that the original source and CGO Media are clearly attributed where appropriate.

How to Cite This Research

A suggested citation format is:

When referencing an individual statistic, researchers should also retain the underlying primary-source attribution shown within the relevant section of this report.

Using the Statistics in Articles and Reports

Individual statistics may be quoted or summarised in:

• News articles.
• Industry reports.
• Academic work.
• Market analysis.
• Presentations.
• Research papers.
• Business reports.

Where possible, link directly to this research page so readers can review the methodology, limitations and original source context.

Using CGO Media Analysis

Interpretive sections such as:

• CGO Media Analysis.
• Enterprise SEO Implications.
• Enterprise SEO Trends UK 2026–2027.
• CGO Media Enterprise Search Visibility Model.
• CGO Media Enterprise SEO Priority Model.

represent CGO Media’s analysis of the underlying evidence.

These should not be presented as conclusions published by the government departments, regulators or technology companies supplying the original data.

Research Methodology

The full CGO Media research approach, evidence standards and source-selection principles are available through our Research Methodology page.

View CGO Media Research Methodology

Press & Media Enquiries

Journalists and media organisations may contact CGO Media regarding:

• Enterprise SEO statistics.
• AI search adoption.
• Google and AI-assisted discovery.
• Enterprise AI adoption.
• Search visibility trends.
• GEO and generative search.
• Digital authority and AI citations.
• Further interpretation of the research.

Additional press resources and research information are available through the CGO Media Press & Media page.

Press & Media Resources

Research Enquiries

Businesses, researchers and organisations wishing to discuss the methodology, datasets or findings may contact CGO Media through the website.

Enquiries relating to bespoke research, enterprise SEO, AI search visibility or GEO should identify the relevant report or data point wherever possible.

Sources & References

The statistics and supporting evidence used in this report were drawn primarily from UK Government departments, Ofcom and first-party platform information.

CGO Media prioritises original statistical publications and primary research sources wherever these are available rather than reproducing figures from secondary SEO or marketing articles.

1. Department for Business and Trade — Business Population Estimates 2025

Publication: Business Population Estimates for the UK and Regions 2025: Statistical Release
Publisher: Department for Business and Trade
Published: 2 October 2025

This publication provides the principal evidence used in Statistics 1–10, including:

• 8,335 large private-sector businesses.
• The 250+ employee definition of a large business.
• 0.15% share of the private-sector business population.
• 11.246 million employees.
• 40% share of private-sector employment.
• £2.696 trillion measured turnover.
• 49% share of measured private-sector turnover.
• Long-term growth in the number of large businesses.
• Large-business industry distribution.

View the Business Population Estimates 2025

Important note: DBT turnover figures exclude Financial and Insurance Activities where comparable turnover information is unavailable.

2. Department for Science, Innovation and Technology — UK Business Data Survey 2026

Publication: UK Business Data Survey 2026
Publisher: Department for Science, Innovation and Technology
Published: 18 June 2026

This is the principal source for Statistics 11–40.

The survey provides large-business evidence covering:

• Website ownership.
• Digitised data use.
• Personal and non-personal data.
• Cookies and digital tracking.
• Data sharing.
• Data analysis.
• Public-cloud use.
• Data-centre infrastructure.
• Artificial-intelligence adoption.
• AI research applications.
• AI data analysis.
• AI code generation.
• Customer-service chatbots.
• AI integration into business systems.
• Automated decision-making.
• AI training data.
• Formal AI policies.
• Data-protection leadership.
• Specialist compliance staff.
• Staff training.
• Compliance burden.
• Server and cloud downtime.
• International data transfers.

View the UK Business Data Survey 2026

3. UK Business Data Survey 2026 — Technical Report

Publication: UK Business Data Survey 2026: Technical Report
Publisher: Department for Science, Innovation and Technology

The technical report provides additional information about:

• Survey methodology.
• Question wording.
• Business-size categories.
• Sampling.
• Definitions.
• AI-use questions.
• Automated decision-making questions.
• Survey routing.

It is particularly useful for understanding what individual AI statistics measure and which businesses were asked each question.

View the UK Business Data Survey 2026 Technical Report

4. Ofcom — From Apps to AI Search: How the UK Goes Online in 2025

Publication: From Apps to AI Search: How the UK Goes Online in 2025
Publisher: Ofcom
Published: 10 December 2025

This Ofcom publication supports several of the search and AI-discovery statistics in Statistics 41–50, including:

• 82% Google Search reach among UK adults.
• Approximately 3 billion Google searches per month.
• Approximately 30% of Google searches displaying AI Overviews.
• 53% of adults often seeing AI-generated search summaries.
• 1.8 billion UK ChatGPT visits during January–August 2025.
• 368 million ChatGPT visits during the equivalent period of 2024.

View From Apps to AI Search

5. Ofcom — Adults’ Media Use and Attitudes 2026

Publication: Adults’ Media Use and Attitudes Report 2026
Publisher: Ofcom
Published: 2 April 2026

The report provides supporting evidence on UK adult media, internet and search behaviour.

It is used within this research for evidence including:

• Search-engine usage among UK online adults.
• UK online behaviour.
• Search interaction and audience measurement.
• Supporting Ipsos iris audience data.

View the Adults’ Media Use and Attitudes 2026 Report

6. Department for Science, Innovation and Technology — Public Engagement Survey 2025/2026

Publication: DSIT Public Engagement Survey 2025/2026
Publisher: Department for Science, Innovation and Technology
Published: 2026

This research supports the generative-AI adoption statistics used in the final section of the report.

Key evidence includes:

• 59% of UK adults used some form of generative AI during the previous three months.
• Generative-AI adoption reached at least 75% among adults below the age of 45.
• 54% of generative-AI users in the online sample reported using it for work purposes.
• 47% identified easier access to information or advice as an AI benefit.
• 74% were concerned AI-generated information might be inaccurate.

View the DSIT Public Engagement Survey 2025/2026

7. Google — Introducing AI Mode in the UK

Publication: Google Search: Introducing AI Mode in the UK
Publisher: Google
Published: 28 July 2025

Google’s first-party announcement is used for evidence relating to the changing structure of conversational search.

Google reported that early AI Mode users were asking questions approximately two to three times the length of traditional search queries.

Google also describes AI Mode as using a query fan-out process that can break more complicated questions into subtopics and issue multiple searches.

View Google’s AI Mode UK Announcement

Source Mapping by Statistics

CGO Media Research Methodology

Further information on CGO Media’s approach to evidence selection, research interpretation and publication standards is available here:

CGO Media Research Methodology