AI Adoption Readiness Scores

This dataset provides a comprehensive benchmark of organizational readiness for AI adoption, combining survey-based scores with digital maturity indicators, leadership support, data quality, and talent availability. It enables organizations, consultants, and researchers to compare AI preparedness across industries, countries, and time, supporting strategic planning and targeted interventions.

  • last updated 21 Aug 2025
  • by GoMask
The brief that made it

Benchmarking AI adoption readiness across organizations

Sample rows

preview · 8 of 200 rows · all 15 columns
organization_idstringdigital_maturity_scorefloatai_strategy_existsbooleanprimary_ai_use_casestringorganization_namestringindustrystringcountrystringsurvey_datedateai_readiness_scorefloatleadership_support_scorefloatdata_quality_scorefloattalent_availability_scorefloatai_projects_countintegerbudget_allocated_aifloatsurvey_responder_rolestring
ORG000196.3trueNetwork OptimizationPacific Quantum SystemsTechnologyUnited States2023-09-1295.797.599.297.91216540000Chief AI Scientist
ORG000292.5trueDrug DiscoveryBlue Ridge PharmaceuticalsPharmaceuticalsSingapore2024-02-0890.891.694.893.21418800000Chief Innovation Officer
ORG000397.1truePredictive MaintenanceGlobal Telecom HoldingsTelecomJapan2023-12-0592.295.997.796.51521700000CTO
ORG000491.4trueProcess AutomationNorthTech AerospaceAerospaceRussia2022-07-1987.394.192.790.888700000CIO
ORG000588.6trueProduct EnhancementSilverwave Software SolutionsSoftwareIsrael2024-05-2185.189.790.591.699400000Chief Technology Officer
ORG000616.7falseblankGreenfield Manufacturing LtdManufacturingGermany2021-11-0615.213.518.819.600Production Manager
ORG00078.2falseblankHorizon Real EstateReal EstateSouth Africa2022-03-3010.19.312.78.900Operations Director
ORG000829.1falseblankOceanic Shipping GroupShippingGreece2023-02-1120.419.824.315.200Logistics Manager

What the 200 rows show

from the 200-row sample
  • 60%ai_strategy_exists = true
  • 58.2median digital_maturity_score
  • 19industries
  • 20countries
  • 59.5median ai_readiness_score
  • 56.0median leadership_support_score
digital_maturity_score200 rows, in bands of 10
020407291919181115222535050100digital_maturity_score →

Median 58.2, from 4.8 to 99.2.

primary_ai_use_case120 rows with a value · 80 left blank
  1. Predictive Maintenance11
  2. Network Optimization9
  3. Fraud Detection8
  4. Personalized Recommendations8
  5. Operations Optimization8
  6. Process Automation7
  7. Product Enhancement7
  8. Claims Automation7
  9. Customer Service Automation6
  10. Drug Discovery5
15 columns by typefrom the column list below
  • string 6
  • integer 1
  • float 6
  • date 1
  • boolean 1

Columns

15 columns in four groups
blueprint · 15 columns
columntypedescriptionexample
Text 6 columns
organization_idstringUnique identifier for the organization being assesseduniqueORG0001
organization_namestringName of the organizationPacific Quantum Systems
industrystringIndustry sector of the organization (e.g., Finance, Healthcare, Retail)Technology
countrystringCountry where the organization is headquarteredUnited States
primary_ai_use_casestringMain business area or function targeted for AI adoption (e.g., customer service, operations, marketing)optionalNetwork Optimization
survey_responder_rolestringRole or job title of the person who completed the survey (e.g., CIO, CTO, Head of Data Science)Chief AI Scientist
Numbers 7 columns
digital_maturity_scorefloatOverall digital maturity score (e.g., 0-100) based on digital infrastructure and capabilities0 to 10096.3
ai_readiness_scorefloatComposite score (e.g., 0-100) representing organizational readiness for AI adoption0 to 10095.7
leadership_support_scorefloatScore (0-100) indicating leadership's support for AI initiatives0 to 10097.5
data_quality_scorefloatScore (0-100) reflecting the quality and accessibility of organizational data0 to 10099.2
talent_availability_scorefloatScore (0-100) for the availability of AI-skilled talent within the organization0 to 10097.9
ai_projects_countintegerNumber of active AI projects or pilots within the organization0 or more12
budget_allocated_aifloatAnnual budget allocated for AI initiatives (in USD)0 or more · optional16540000
Dates and times 1 column
survey_datedateDate when the AI readiness survey was completed2023-09-12
True or false 1 column
ai_strategy_existsbooleanIndicates whether the organization has a formal AI adoption strategytrue

Use it for

  • ai strategy ex…60%120 of 200 rows

    A technology dashboard

    The ai_strategy_exists rate, digital_maturity_score and a breakdown of primary_ai_use_case. Excel, Power BI or Tableau.

  • Why do 120 of 200 rows have ai_strategy_exists = true?

    A class exercise

    Hand out the rows and one question. Everyone works from the same 200 rows.

  • A software demo

    Believable organizations with organization_name, industry and country to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 15 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset200 rows15 columns
Yours1,000 rows15 columnscountry: UK only

blueprint · ai-adoption-readiness-scores

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 15 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each row is an organization’s score record
  • Include size, industry, digital maturity, and AI training participation
  • Capture readiness score and adoption intent
  • Exclude incomplete survey responses
Rows
Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
ai-adoption-readiness-scores

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