Methodology
Research Design
The UK Enterprise GenAI Adoption Benchmark employs a mixed-methods research design, combining quantitative survey data with qualitative insights from follow-up interviews. This approach enables comprehensive analysis of both the extent and nature of GenAI adoption across UK enterprises.
Sample
The target population comprises UK-based organisations of all sizes across all industry sectors. Participation is voluntary and open to organisations meeting the following criteria:
- Headquartered in the United Kingdom
- Have operational teams based in the UK
- Have begun exploring or implementing generative AI initiatives
We aim for a representative sample across organisation sizes, sectors, and geographical regions within the UK. Stratified sampling ensures adequate representation across key segments for meaningful comparative analysis.
Data Collection
Survey Instrument
The survey comprises approximately 40 questions across seven domains. Questions include:
- Multiple choice questions for quantitative analysis
- Rating scales for assessing maturity and satisfaction
- Open-ended questions for qualitative insights
- Conditional branching based on prior responses
The survey typically takes 15-20 minutes to complete. Participants may save progress and return to complete the survey at their convenience.
Data Quality & Validation
Multiple measures ensure data quality and validity:
- Pre-validation: Questions reviewed by subject matter experts and pilot tested with a small sample of organisations
- In-built validation: Response validation for required fields and logical consistency checks
- Post-collection validation: Automated checks for complete responses and outlier detection
- Manual review: Sample of responses reviewed for quality and consistency
Data Analysis
Quantitative Analysis
Quantitative data undergoes statistical analysis including:
- Descriptive statistics (means, medians, distributions)
- Correlation analysis between variables
- Comparative analysis across segments (size, sector, region)
- Trend analysis where longitudinal data is available
Qualitative Analysis
Open-ended responses are analysed using thematic analysis to identify common themes, patterns, and insights that complement the quantitative findings.
Anonymisation & Privacy
All data is anonymised prior to analysis:
- Organisation identifiers are replaced with anonymous codes
- Personally identifiable information is stored separately
- Small group reporting follows k-anonymity principles (N≥10)
- Direct quotes are anonymised and attributed generically
See our Data & Privacy page for detailed information about data handling and protection.
Limitations
Several limitations should be noted when interpreting findings:
- Self-reported data: Responses reflect participants' perceptions and may be subject to bias
- Non-response bias: Organisations that choose to participate may differ from those that do not
- Rapid evolution: The GenAI landscape changes quickly; findings represent a snapshot in time
- UK focus: Findings may not be directly applicable to other geographical contexts
Definitions
Generative AI
For the purposes of this benchmark, "generative AI" refers to artificial intelligence systems capable of creating new content—including text, images, code, audio, and other media—in response to prompts or requests. This includes large language models, image generation tools, code generation systems, and similar technologies.
In Production
"In production" refers to GenAI tools and systems that are actively used in operational business processes, delivering value to end users or customers. This excludes: exploratory experiments, proof-of-concept projects, and tools used only by research or development teams without broader organisational deployment.
Enterprise
"Enterprise" refers to organisations with established business operations, including corporations, public sector bodies, non-profit organisations, and other entities with formal structures and operational capabilities.