MARKETHINK RESEARCH LEDGER
AI marketing statistics, with the source behind every number.
A selective, reviewable collection of 60 statistics from 9 original sources, with sample context, dates, definitions, and limits preserved.
FOUR NUMBERS TO START WITH
The useful story is adoption plus operating discipline.
18%US firms that used AI in a business function during the supplement reference period.
95%B2B marketers saying their organizations use AI-powered applications.
83%US ad executives saying their company had deployed AI in the creative process.
73.4%Marketers who saw AI working with marketers and assisting with most job duties.
MARKETHINK ANALYSIS
Four conclusions the data can support.
Adoption is not one number.
Firm-level surveys, marketing-team surveys, and vendor studies count different behaviors. Treat the definition as part of the statistic.
Broad use can coexist with shallow deployment.
High “any use” figures sit beside lower organization-wide deployment figures. Experimentation is not the same as an embedded operating system.
Content is common. Measurement is less mature.
Writing and creative tools lead use cases, while measurement frameworks and causal outcome evidence remain limited.
Human judgment shows up as a control, not a slogan.
Augmentation, disclosure, escalation, and differentiated human content recur across independent studies.
01 / 09
Adoption is broad. Deployment is not the same thing.
These figures use different units: firms, employees, marketing teams, pilots, and organization-wide deployment. Read the scope before comparing the percentages.
US firms that used AI in a business function during the supplement reference period.
- Evidence
- observed adoption
- Study
- United States; November 2025 to January 2026
- Sample
- Nationally representative Business Trends and Outlook Survey AI supplement; exact n not stated on the summary page
- Context
- Firm adoption, employment-weighted adoption, and worker task use are different measures. The survey does not isolate marketing departments.
US firm AI use on an employment-weighted basis during the same period.
- Evidence
- observed adoption
- Study
- United States; November 2025 to January 2026
- Sample
- Nationally representative Business Trends and Outlook Survey AI supplement; exact n not stated on the summary page
- Context
- Employment weighting answers a different question from the 18% firm-level estimate by giving more influence to larger employers.
US firms expected to use AI in a business function within six months.
- Evidence
- projection
- Study
- United States; November 2025 to January 2026
- Sample
- Nationally representative Business Trends and Outlook Survey AI supplement; exact n not stated on the summary page
- Context
- This is a stated expectation, not observed future adoption.
AI-using firms that integrated AI into three or fewer business functions.
- Evidence
- observed adoption
- Study
- United States; November 2025 to January 2026
- Sample
- Nationally representative Business Trends and Outlook Survey AI supplement; exact n not stated on the summary page
- Context
- Firm adoption, employment-weighted adoption, and worker task use are different measures. The survey does not isolate marketing departments.
US firms reporting that workers used AI in work-related tasks.
- Evidence
- observed adoption
- Study
- United States; November 2025 to January 2026
- Sample
- Nationally representative Business Trends and Outlook Survey AI supplement; exact n not stated on the summary page
- Context
- Firm adoption, employment-weighted adoption, and worker task use are different measures. The survey does not isolate marketing departments.
Firms across OECD countries with available data that reported using AI in 2025.
- Evidence
- observed adoption
- Study
- OECD countries where data were available; 2025
- Sample
- National business ICT surveys compiled in the OECD ICT Access and Usage Database; n varies by country
- Context
- Coverage is limited to countries with available data. Definitions and business-size thresholds can vary by national source.
B2B marketers describing their organizations as exploratory or developing in AI implementation.
- Evidence
- observed adoption
- Study
- Global, mostly North America; June 24 to August 14, 2025
- Sample
- 1,015 B2B marketers from 1,229 global responses
- Context
- This combines the report's 20% exploratory and 48% developing categories.
Organizations that had embedded agentic AI organization-wide for customer support.
- Evidence
- scaled deployment
- Study
- North America, Latin America, Europe, APAC and the Middle East; October to November 2025
- Sample
- 3,000 executives and CX practitioners plus 4,000 customers
- Context
- Business results are self-reported by executives and CX practitioners at organizations with at least $250 million in revenue. Customer results are a separate sample.
Organizations that had embedded agentic AI organization-wide for brand discovery and search.
- Evidence
- scaled deployment
- Study
- North America, Latin America, Europe, APAC and the Middle East; October to November 2025
- Sample
- 3,000 executives and CX practitioners plus 4,000 customers
- Context
- Business results are self-reported by executives and CX practitioners at organizations with at least $250 million in revenue. Customer results are a separate sample.
US ad executives saying their company had deployed AI in the creative process.
- Evidence
- observed adoption
- Study
- United States; October 2025 to January 2026
- Sample
- 505 Gen Z and Millennial consumers plus 104 ad industry executives
- Context
- The executive sample is small and limited to companies spending at least $1 million annually on media. Consumer findings cover Gen Z and Millennials only.
Respondents saying their organizations regularly used AI in at least one business function.
- Evidence
- observed adoption
- Study
- 105 nations; June 25 to July 29, 2025
- Sample
- 1,993 survey participants
- Context
- Results are self-reported and weighted by national GDP. Organization-wide AI use is broader than marketing use.
Respondents saying their organizations were scaling an agentic AI system somewhere in the enterprise.
- Evidence
- scaled deployment
- Study
- 105 nations; June 25 to July 29, 2025
- Sample
- 1,993 survey participants
- Context
- Results are self-reported and weighted by national GDP. Organization-wide AI use is broader than marketing use.
Respondents saying their organizations had begun experimenting with AI agents.
- Evidence
- experimentation
- Study
- 105 nations; June 25 to July 29, 2025
- Sample
- 1,993 survey participants
- Context
- Results are self-reported and weighted by national GDP. Organization-wide AI use is broader than marketing use.
Respondents saying their organizations were scaling AI programs across the organization.
- Evidence
- scaled deployment
- Study
- 105 nations; June 25 to July 29, 2025
- Sample
- 1,993 survey participants
- Context
- The report describes this as roughly one-third and shows larger companies scaling more often.
02 / 09
Small-business use depends on what the survey counts.
A survey asking about any business AI use can produce a very different number from one asking about AI in marketing. Both can be accurate within their definitions.
Small firms across covered OECD countries that reported using AI in 2025.
- Evidence
- observed adoption
- Study
- OECD countries where data were available; 2025
- Sample
- National business ICT surveys compiled in the OECD ICT Access and Usage Database; n varies by country
- Context
- Coverage is limited to countries with available data. Definitions and business-size thresholds can vary by national source.
Large firms across covered OECD countries that reported using AI in 2025.
- Evidence
- observed adoption
- Study
- OECD countries where data were available; 2025
- Sample
- National business ICT surveys compiled in the OECD ICT Access and Usage Database; n varies by country
- Context
- This is a size comparison, not evidence that firm size alone causes adoption.
US small-business owners who said they currently use AI technologies for business activity.
- Evidence
- observed adoption
- Study
- United States; 2025; exact field dates not stated in the report text
- Sample
- 521 employer responses overall; AI-use questions use smaller bases, including n=118, n=119, and n=110
- Context
- The sample is drawn from NFIB members, and several AI-use findings apply only to the smaller subset of current users.
Nonusers who said they did not plan to use AI for business purposes in the next 12 months.
- Evidence
- stated intention
- Study
- United States; 2025; exact field dates not stated in the report text
- Sample
- 521 employer responses overall; AI-use questions use smaller bases, including n=118, n=119, and n=110
- Context
- The base is respondents not currently using AI, n=385 for the table containing this question.
Current small-business AI users who used or planned to use AI for marketing or advertising.
- Evidence
- observed adoption
- Study
- United States; 2025; exact field dates not stated in the report text
- Sample
- 521 employer responses overall; AI-use questions use smaller bases, including n=118, n=119, and n=110
- Context
- The use-case table has n=118, much smaller than the overall sample.
US SMB respondents reported as adopting AI in marketing by April 2026, up from 26% in 2023.
- Evidence
- observed adoption
- Study
- United States, United Kingdom, Canada, Australia and New Zealand; Q2 2026; US adoption figure measured by April 2026
- Sample
- 3,340 SMB respondents and 2,255 consumer respondents
- Context
- The release does not publish the full question wording. The broad marketing adoption measure should not be compared directly with NFIB current business use.
03 / 09
Marketing is a leading business use case.
The strongest evidence points to active use across sales and marketing, but the maturity of that use varies from experimentation to embedded workflows.
AI-using firms that deployed AI in sales and marketing, the most common function reported.
- Evidence
- observed adoption
- Study
- United States; November 2025 to January 2026
- Sample
- Nationally representative Business Trends and Outlook Survey AI supplement; exact n not stated on the summary page
- Context
- Firm adoption, employment-weighted adoption, and worker task use are different measures. The survey does not isolate marketing departments.
B2B marketers saying their organizations use AI-powered applications.
- Evidence
- observed adoption
- Study
- Global, mostly North America; June 24 to August 14, 2025
- Sample
- 1,015 B2B marketers from 1,229 global responses
- Context
- Results are self-reported. The research was sponsored by a marketing technology company, and the B2B sample was mostly North American.
Marketing teams saying they use AI in at least a few marketing areas.
- Evidence
- observed adoption
- Study
- Global; Not stated on the public report page
- Sample
- More than 1,500 B2B and B2C marketers
- Context
- Results are self-reported, and the public page does not disclose detailed sampling or field dates. Extensive and occasional use are separate response categories.
04 / 09
Content is the entry point. Campaign operations are wider.
Copy and creative production lead current usage. Social, SEO, email, and advertising workflows show where AI is moving beyond a single drafting tool.
Task-level AI adopters reporting generative AI use for writing and editing.
- Evidence
- observed adoption
- Study
- United States; November 2025 to January 2026
- Sample
- Nationally representative Business Trends and Outlook Survey AI supplement; exact n not stated on the summary page
- Context
- The base is firms reporting task-level adoption, not all firms.
Current small-business AI users who used or planned to use AI for communications such as email, memos, or documents.
- Evidence
- observed adoption
- Study
- United States; 2025; exact field dates not stated in the report text
- Sample
- 521 employer responses overall; AI-use questions use smaller bases, including n=118, n=119, and n=110
- Context
- The use-case table has n=118, much smaller than the overall sample.
AI-using B2B marketers using content tools to generate or optimize copy.
- Evidence
- observed adoption
- Study
- Global, mostly North America; June 24 to August 14, 2025
- Sample
- 1,015 B2B marketers from 1,229 global responses
- Context
- Results are self-reported. The research was sponsored by a marketing technology company, and the B2B sample was mostly North American.
AI-using B2B marketers using tools to generate or edit creative assets.
- Evidence
- observed adoption
- Study
- Global, mostly North America; June 24 to August 14, 2025
- Sample
- 1,015 B2B marketers from 1,229 global responses
- Context
- Results are self-reported. The research was sponsored by a marketing technology company, and the B2B sample was mostly North American.
AI-using B2B marketers using AI-powered SEO tools.
- Evidence
- observed adoption
- Study
- Global, mostly North America; June 24 to August 14, 2025
- Sample
- 1,015 B2B marketers from 1,229 global responses
- Context
- Results are self-reported. The research was sponsored by a marketing technology company, and the B2B sample was mostly North American.
AI-using B2B marketers using AI-powered social media tools.
- Evidence
- observed adoption
- Study
- Global, mostly North America; June 24 to August 14, 2025
- Sample
- 1,015 B2B marketers from 1,229 global responses
- Context
- Results are self-reported. The research was sponsored by a marketing technology company, and the B2B sample was mostly North American.
Ad executives whose companies used AI for social-media ads.
- Evidence
- observed adoption
- Study
- United States; October 2025 to January 2026
- Sample
- 505 Gen Z and Millennial consumers plus 104 ad industry executives
- Context
- The executive sample is small and limited to companies spending at least $1 million annually on media. Consumer findings cover Gen Z and Millennials only.
Ad executives whose companies used AI for display ads.
- Evidence
- observed adoption
- Study
- United States; October 2025 to January 2026
- Sample
- 505 Gen Z and Millennial consumers plus 104 ad industry executives
- Context
- The executive sample is small and limited to companies spending at least $1 million annually on media. Consumer findings cover Gen Z and Millennials only.
Marketers using AI extensively or occasionally for content creation, respectively.
- Evidence
- observed adoption
- Study
- Global; Not stated on the public report page
- Sample
- More than 1,500 B2B and B2C marketers
- Context
- The two values are separate response categories and should not be presented as a single 80.5% estimate without the full questionnaire.
Marketers using AI extensively or occasionally for advertising automation and optimization, respectively.
- Evidence
- observed adoption
- Study
- Global; Not stated on the public report page
- Sample
- More than 1,500 B2B and B2C marketers
- Context
- The two values are separate response categories and should not be presented as a single 70.6% estimate without the full questionnaire.
05 / 09
Lead and follow-up evidence needs careful attribution.
Survey respondents report improved lead generation and growing use in email. These are useful operating signals, not proof that AI caused the outcome.
AI-using B2B marketers using AI-powered email marketing tools.
- Evidence
- observed adoption
- Study
- Global, mostly North America; June 24 to August 14, 2025
- Sample
- 1,015 B2B marketers from 1,229 global responses
- Context
- Results are self-reported. The research was sponsored by a marketing technology company, and the B2B sample was mostly North American.
Organizations reporting that lead generation performance somewhat or significantly improved over the prior three years.
- Evidence
- self-reported outcome
- Study
- North America, Latin America, Europe, APAC and the Middle East; October to November 2025
- Sample
- 3,000 executives and CX practitioners plus 4,000 customers
- Context
- Business results are self-reported by executives and CX practitioners at organizations with at least $250 million in revenue. Customer results are a separate sample.
06 / 09
Human review remains part of the operating model.
Respondents consistently point to augmentation, disclosure, and escalation to people. This is evidence about preferred controls and working models, not a universal rule for every task.
Firms experiencing AI-related task effects that used AI only to augment tasks.
- Evidence
- observed operating model
- Study
- United States; November 2025 to January 2026
- Sample
- Nationally representative Business Trends and Outlook Survey AI supplement; exact n not stated on the summary page
- Context
- Firm adoption, employment-weighted adoption, and worker task use are different measures. The survey does not isolate marketing departments.
Current small-business AI users reporting no change in employee count.
- Evidence
- self-reported outcome
- Study
- United States; 2025; exact field dates not stated in the report text
- Sample
- 521 employer responses overall; AI-use questions use smaller bases, including n=118, n=119, and n=110
- Context
- The employment table has n=119. This does not predict future workforce effects.
Organizations ranking clear disclosure of AI interactions among the most important factors for building trust in agentic AI.
- Evidence
- organizational priority
- Study
- North America, Latin America, Europe, APAC and the Middle East; October to November 2025
- Sample
- 3,000 executives and CX practitioners plus 4,000 customers
- Context
- Business results are self-reported by executives and CX practitioners at organizations with at least $250 million in revenue. Customer results are a separate sample.
Organizations ranking easy escalation to human support among the most important trust factors for agentic AI.
- Evidence
- organizational priority
- Study
- North America, Latin America, Europe, APAC and the Middle East; October to November 2025
- Sample
- 3,000 executives and CX practitioners plus 4,000 customers
- Context
- Business results are self-reported by executives and CX practitioners at organizations with at least $250 million in revenue. Customer results are a separate sample.
Marketers who saw AI working with marketers and assisting with most job duties.
- Evidence
- respondent opinion
- Study
- Global; Not stated on the public report page
- Sample
- More than 1,500 B2B and B2C marketers
- Context
- Results are self-reported, and the public page does not disclose detailed sampling or field dates. Extensive and occasional use are separate response categories.
Marketers who believed more unique, human-centered content is needed to compete with AI content.
- Evidence
- respondent opinion
- Study
- Global; Not stated on the public report page
- Sample
- More than 1,500 B2B and B2C marketers
- Context
- Results are self-reported, and the public page does not disclose detailed sampling or field dates. Extensive and occasional use are separate response categories.
07 / 09
Investment is moving toward AI, with scrutiny attached.
The available budget figure records stated 2026 priorities. It should not be read as realized spend or return on investment.
B2B marketers who put AI-powered marketing tools among their top three areas for increased 2026 investment.
- Evidence
- stated investment plan
- Study
- Global, mostly North America; June 24 to August 14, 2025
- Sample
- 1,015 B2B marketers from 1,229 global responses
- Context
- Results are self-reported. The research was sponsored by a marketing technology company, and the B2B sample was mostly North American.
08 / 09
Trust, governance, and measurement are still unresolved.
Consumers and advertisers do not always see AI-generated marketing the same way. Disclosure, measurement frameworks, and content quality remain material constraints.
Consumers globally who wanted businesses to explicitly label AI-generated content.
- Evidence
- consumer preference
- Study
- United States, United Kingdom, Canada, Australia and New Zealand; Q2 2026; US adoption figure measured by April 2026
- Sample
- 3,340 SMB respondents and 2,255 consumer respondents
- Context
- The publisher sells marketing technology. The release uses a broad SMB marketing AI adoption measure that is not directly comparable with the NFIB business-use question.
SMBs globally reported as fully transparent about their AI use.
- Evidence
- self-reported practice
- Study
- United States, United Kingdom, Canada, Australia and New Zealand; Q2 2026; US adoption figure measured by April 2026
- Sample
- 3,340 SMB respondents and 2,255 consumer respondents
- Context
- The publisher sells marketing technology. The release uses a broad SMB marketing AI adoption measure that is not directly comparable with the NFIB business-use question.
B2B marketers reporting that content quality decreased with AI.
- Evidence
- self-reported outcome
- Study
- Global, mostly North America; June 24 to August 14, 2025
- Sample
- 1,015 B2B marketers from 1,229 global responses
- Context
- Results are self-reported. The research was sponsored by a marketing technology company, and the B2B sample was mostly North American.
Customers who said they would disengage after discovering content was AI-generated.
- Evidence
- consumer stated response
- Study
- North America, Latin America, Europe, APAC and the Middle East; October to November 2025
- Sample
- 3,000 executives and CX practitioners plus 4,000 customers
- Context
- Business results are self-reported by executives and CX practitioners at organizations with at least $250 million in revenue. Customer results are a separate sample.
Customers who said they would disengage after learning they were interacting with AI when expecting a person.
- Evidence
- consumer stated response
- Study
- North America, Latin America, Europe, APAC and the Middle East; October to November 2025
- Sample
- 3,000 executives and CX practitioners plus 4,000 customers
- Context
- Business results are self-reported by executives and CX practitioners at organizations with at least $250 million in revenue. Customer results are a separate sample.
Organizations with a measurement framework implemented for generative AI.
- Evidence
- observed governance practice
- Study
- North America, Latin America, Europe, APAC and the Middle East; October to November 2025
- Sample
- 3,000 executives and CX practitioners plus 4,000 customers
- Context
- Business results are self-reported by executives and CX practitioners at organizations with at least $250 million in revenue. Customer results are a separate sample.
Ad executives who believed young consumers felt positive about AI-generated ads, compared with the share of surveyed consumers who actually reported positive sentiment.
- Evidence
- perception gap
- Study
- United States; October 2025 to January 2026
- Sample
- 505 Gen Z and Millennial consumers plus 104 ad industry executives
- Context
- This is a 37-point perception gap across two survey groups, not a causal result.
Gen Z consumers reporting negative sentiment toward AI-generated ads, compared with Millennials.
- Evidence
- consumer sentiment
- Study
- United States; October 2025 to January 2026
- Sample
- 505 Gen Z and Millennial consumers plus 104 ad industry executives
- Context
- The executive sample is small and limited to companies spending at least $1 million annually on media. Consumer findings cover Gen Z and Millennials only.
Gen Z and Millennial consumers saying AI disclosure would increase or make no difference to purchase likelihood.
- Evidence
- stated purchase response
- Study
- United States; October 2025 to January 2026
- Sample
- 505 Gen Z and Millennial consumers plus 104 ad industry executives
- Context
- This combines two response categories and does not mean disclosure increases purchases for 73%.
09 / 09
Most outcome data is self-reported, not causal.
Productivity, quality, personalization, lead, and retention findings describe what respondents observed. They do not isolate AI from strategy, staffing, channels, or market conditions.
AI-using firms reporting AI-related employment decreases.
- Evidence
- observed outcome
- Study
- United States; November 2025 to January 2026
- Sample
- Nationally representative Business Trends and Outlook Survey AI supplement; exact n not stated on the summary page
- Context
- The report also cautions against causal interpretation of its regression evidence.
Current small-business AI users reporting increased productivity.
- Evidence
- self-reported outcome
- Study
- United States; 2025; exact field dates not stated in the report text
- Sample
- 521 employer responses overall; AI-use questions use smaller bases, including n=118, n=119, and n=110
- Context
- The impact table has n=110 and does not establish causation.
Current small-business AI users reporting improved product or service quality.
- Evidence
- self-reported outcome
- Study
- United States; 2025; exact field dates not stated in the report text
- Sample
- 521 employer responses overall; AI-use questions use smaller bases, including n=118, n=119, and n=110
- Context
- The impact table has n=110 and does not establish causation.
Current small-business AI users reporting lower operating costs.
- Evidence
- self-reported outcome
- Study
- United States; 2025; exact field dates not stated in the report text
- Sample
- 521 employer responses overall; AI-use questions use smaller bases, including n=118, n=119, and n=110
- Context
- The impact table has n=110 and does not establish causation.
SMB AI users globally naming time savings as the primary benefit.
- Evidence
- self-reported outcome
- Study
- United States, United Kingdom, Canada, Australia and New Zealand; Q2 2026; US adoption figure measured by April 2026
- Sample
- 3,340 SMB respondents and 2,255 consumer respondents
- Context
- The publisher sells marketing technology. The release uses a broad SMB marketing AI adoption measure that is not directly comparable with the NFIB business-use question.
B2B marketers reporting improved operational efficiency from AI.
- Evidence
- self-reported outcome
- Study
- Global, mostly North America; June 24 to August 14, 2025
- Sample
- 1,015 B2B marketers from 1,229 global responses
- Context
- Results are self-reported. The research was sponsored by a marketing technology company, and the B2B sample was mostly North American.
B2B marketers reporting improved content quality from AI.
- Evidence
- self-reported outcome
- Study
- Global, mostly North America; June 24 to August 14, 2025
- Sample
- 1,015 B2B marketers from 1,229 global responses
- Context
- Results are self-reported. The research was sponsored by a marketing technology company, and the B2B sample was mostly North American.
Organizations reporting that personalization performance somewhat or significantly improved over the prior three years.
- Evidence
- self-reported outcome
- Study
- North America, Latin America, Europe, APAC and the Middle East; October to November 2025
- Sample
- 3,000 executives and CX practitioners plus 4,000 customers
- Context
- Business results are self-reported by executives and CX practitioners at organizations with at least $250 million in revenue. Customer results are a separate sample.
Organizations reporting that customer retention performance somewhat or significantly improved over the prior three years.
- Evidence
- self-reported outcome
- Study
- North America, Latin America, Europe, APAC and the Middle East; October to November 2025
- Sample
- 3,000 executives and CX practitioners plus 4,000 customers
- Context
- Business results are self-reported by executives and CX practitioners at organizations with at least $250 million in revenue. Customer results are a separate sample.
HOW THIS RESOURCE WAS BUILT
Methodology and limitations
Inclusion standard
We included a number only when it appeared in an original government dataset, official research report, original survey, or the publisher’s own report page. Secondary statistics roundups were not used as evidence.
Verification standard
Each source URL was loaded during the September 12, 2026 review. Every displayed number is mapped to a ledger ID, publisher, research period, geography, sample note, evidence type, and limitation.
What the page does not claim
Self-reported improvement does not prove causation. Stated plans are not realized adoption. Opinions and preferences are not measured business outcomes. Unlike survey questions are not averaged together.
Curator role
Markethink is the curator and analyst, not the original source of third-party statistics. Our analysis is labeled and kept separate from source findings.
Known limits
- Definitions of AI, generative AI, and agentic AI vary by study.
- Several sources are vendor-sponsored or vendor-published and rely on self-reported responses.
- Global surveys do not automatically represent every country or small business.
- Some subgroup findings use much smaller samples than the headline survey.
- This page is a dated evidence review, not a live market counter.
MACHINE-READABLE
Audit the dataset yourself.
The downloads contain all 60 rows and their research context.
PRIMARY SOURCE INDEX
Nine original sources, with their boundaries.
- S1
The Microstructure of AI Diffusion: Evidence from Firms, Business Functions, and Worker Tasks
U.S. Census Bureau, Center for Economic Studies · 2026-04 · United States
- Research period
- November 2025 to January 2026
- Sample
- Nationally representative Business Trends and Outlook Survey AI supplement; exact n not stated on the summary page
- Source type
- Government statistical working paper
- Limitation
- Firm adoption, employment-weighted adoption, and worker task use are different measures. The survey does not isolate marketing departments.
- S2
AI use by individuals surges across the OECD as adoption by firms continues to expand
OECD · 2026-01-28 · OECD countries where data were available
- Research period
- 2025
- Sample
- National business ICT surveys compiled in the OECD ICT Access and Usage Database; n varies by country
- Source type
- Official intergovernmental statistics
- Limitation
- Coverage is limited to countries with available data. Definitions and business-size thresholds can vary by national source.
- S3
Small Business and Technology 2025
NFIB Research Center · 2025-06 · United States
- Research period
- 2025; exact field dates not stated in the report text
- Sample
- 521 employer responses overall; AI-use questions use smaller bases, including n=118, n=119, and n=110
- Source type
- Original small-business association survey
- Limitation
- The sample is drawn from NFIB members, and several AI-use findings apply only to the smaller subset of current users.
- S4
The Rise of the SMB Creator: Q2 2026 Small Business Now report findings
Constant Contact · 2026-06-10 · United States, United Kingdom, Canada, Australia and New Zealand
- Research period
- Q2 2026; US adoption figure measured by April 2026
- Sample
- 3,340 SMB respondents and 2,255 consumer respondents
- Source type
- Original vendor-commissioned SMB and consumer survey
- Limitation
- The publisher sells marketing technology. The release uses a broad SMB marketing AI adoption measure that is not directly comparable with the NFIB business-use question.
- S5
B2B Content and Marketing Trends: Insights for 2026
Content Marketing Institute and MarketingProfs · 2025-10 · Global, mostly North America
- Research period
- June 24 to August 14, 2025
- Sample
- 1,015 B2B marketers from 1,229 global responses
- Source type
- Original industry survey
- Limitation
- Results are self-reported. The research was sponsored by a marketing technology company, and the B2B sample was mostly North American.
- S6
Adobe 2026 AI and Digital Trends Report
Adobe and Oxford Economics · 2026; exact day not stated on the main report page · North America, Latin America, Europe, APAC and the Middle East
- Research period
- October to November 2025
- Sample
- 3,000 executives and CX practitioners plus 4,000 customers
- Source type
- Original global business and consumer survey
- Limitation
- Business results are self-reported by executives and CX practitioners at organizations with at least $250 million in revenue. Customer results are a separate sample.
- S7
The AI Ad Gap Widens
IAB and Sonata Insights · 2026; exact day not stated on the report page · United States
- Research period
- October 2025 to January 2026
- Sample
- 505 Gen Z and Millennial consumers plus 104 ad industry executives
- Source type
- Original advertising industry and consumer survey
- Limitation
- The executive sample is small and limited to companies spending at least $1 million annually on media. Consumer findings cover Gen Z and Millennials only.
- S8
The state of AI in 2025: Agents, innovation, and transformation
McKinsey & Company, QuantumBlack · 2025-11 · 105 nations
- Research period
- June 25 to July 29, 2025
- Sample
- 1,993 survey participants
- Source type
- Original global executive and practitioner survey
- Limitation
- Results are self-reported and weighted by national GDP. Organization-wide AI use is broader than marketing use.
- S9
2026 State of Marketing
HubSpot · 2026; exact day not stated on the report page · Global
- Research period
- Not stated on the public report page
- Sample
- More than 1,500 B2B and B2C marketers
- Source type
- Original vendor marketing survey
- Limitation
- Results are self-reported, and the public page does not disclose detailed sampling or field dates. Extensive and occasional use are separate response categories.
DEFINITIONS
Glossary
- AI adoption
- A respondent reports using an AI technology. This can range from one task to organization-wide use.
- Experimentation or pilot
- Limited testing that has not necessarily reached standard workflows or broad deployment.
- Scaled deployment
- Use expanded across a function or organization. Each source’s exact definition still applies.
- Generative AI
- Systems that create text, images, audio, video, or other outputs from prompts or data.
- Agentic AI
- Systems described by a source as taking autonomous or semi-autonomous actions across steps in a workflow.
- Self-reported outcome
- An improvement or decline described by a respondent, without experimental proof that AI caused it.
- Employment-weighted
- A measure that gives larger employers more influence than a simple count of firms.
UPDATE LOG
Substantive changes only.
Initial research edition prepared with 60 verified statistics from 9 original sources. No date rotation or simulated freshness.
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