References
The evidence behind the readiness check
Every framework and finding the check draws on, in one place, for anyone who wants to check it for themselves.
The theory behind this check
A two page explainer of the two ladders the check measures, and why reading only one of them hides half the picture.
Learn more about the framework (PDF, 2 pages)Frameworks
The check's two ladders, organisational maturity and individual competency, draw on the following published frameworks.
- OECD and European Commission, Empowering Learners for the Age of AI (the AI Literacy Framework), 2026https://www.oecd.org/en/publications/empowering-learners-for-the-age-of-ai_65cd27d4-en.html
- Software Engineering Institute (Carnegie Mellon University) with Accenture, AI Adoption Maturity Model, 2026https://www.sei.cmu.edu/news/sei-and-accenture-release-ai-adoption-maturity-model-to-help-organizations-scale-ai-with-predictable-outcomes/
- Cosgrove, J. and Cachia, R., DigComp 3.0: European Digital Competence Framework, 5th edition, Publications Office of the European Union, Luxembourg, 2025https://data.europa.eu/doi/10.2760/0001149
- Dakan, R. and Feller, J., Framework for AI Fluency, v1.1, January 2025https://ringling.libguides.com/ai/framework
Note: the OECD/EC framework is written for primary and secondary schools specifically, adapted here for organisations more broadly.
Sport-door evidence
One additional source informs the sport-specific framing of the check.
- N3XT Sports, 2026 Digital Trends in the Sports Industry, May 2026https://www.n3xtsports.com/report-2026-digital-trends-in-the-sports-industry/
Findings cited in your report
Depending on the pattern your answers produce, your full report cites one of the following.
Stranded skill
A survey of 600 professionals by Carnegie Mellon's Software Engineering Institute with Accenture, January 2026, found 61 percent of organisations hold a formal AI strategy that is not fully implemented, and named insufficient knowledgeable staff and lack of appropriate data as the two largest drags on adoption.
Source: AI Adoption Maturity Model, SEI with Accenture, 2026https://www.sei.cmu.edu/news/sei-and-accenture-release-ai-adoption-maturity-model-to-help-organizations-scale-ai-with-predictable-outcomes/
Idle capability
The Global SportsTech Report 2026 found that 21 percent of organisations already using AI name in-house skills as the single biggest barrier to going further, and lists legacy systems, skills gaps and internal resistance ahead of the technology itself.
Source: Global SportsTech Report 2026, SportsPro with Sportradarhttps://www.sportspro.com/projects/global-sportstech-report/
Matched
McKinsey's May 2026 survey of 8,019 employees and 981 employers across ten European countries found demand for practical AI fluency up fivefold since late 2023, against 1.7 times for technical AI skills.
Source: Agents, robots, and us, McKinsey Global Institute, May 2026https://www.mckinsey.com/mgi/our-research/agents-robots-and-us-how-ai-reshapes-work-and-skills-in-europe
Related research
Consulted alongside the SHARE 2.0 policy paper work. These didn't shape a specific item or citation on the check, but sit in the same space and are listed here for completeness.
- PARIS21 (Partnership in Statistics for Development in the 21st Century) with the Task Team on AI for Official Statistics, The AI Readiness Self-Assessment: A Practical Guide for NSOs, v1.0, 2026https://www.paris21.org/knowledge-base/ai-readiness-self-assessment-practical-guide-nsos
- UNESCO, AI competency framework for teachers, 2024https://www.unesco.org/en/articles/ai-competency-framework-teachers
- UNESCO, AI competency framework for students, 2024https://www.unesco.org/en/articles/what-you-need-know-about-unescos-new-ai-competency-frameworks-students-and-teachers
- Falese, A., Di Palma, D., Digennaro, S. and Merten, D., "Digital Transformation in Sport Organizations: Toward a Conceptual Framework," Societies 2026, 16, 175https://doi.org/10.3390/soc16060175