Case studies
How partners are driving systemic change through the Reskilling Revolution
New Economy Skills
Real‑world examples of governments, employers and educators aligning skill-building with market demand and credentialing five critical skill families using skills-first practices and shared standards:
- Maker
- Energy and Sustainability (Coming - 2026)
- Business and Entrepreneurship (Coming - 2027)
Innovative Skills Funding Models
Members of the World Economic Forum Future Skills Alliance identified global initiatives that adopt collaborative and innovative approaches to funding skills development, upskilling and reskilling in a wide range of contexts.
These innovative public–private approaches explore continuous learning affordability by fairly sharing costs across individuals, employers and governments through sustainable financing models.
Global Skills Taxonomy Adoption
The Global Skills Taxonomy Adoption Toolkit equips leaders across sectors—businesses, governments, and education providers—with actionable steps, evidence-based insights, and real-world case studies to adopt a common skills language and embed skills-first approaches into talent management strategies.
Actionable guidance and cases showing how organizations map roles and learning to a common skills taxonomy and apply it across hiring, development and workforce planning.
![Context: EY is building an AI-ready firm from the inside out by equipping people to use AI confidently and responsibly, strengthening core delivery and opening new client services. The goal is simple: practice, build and recognize AI skills in real time, not just track completion results. The strategy makes skills visible and portable across geographies and service lines by combining role-based learning, evidence-backed credentials and clear standards for responsible use. Approach: A Skills Profile enables the connection of credentials to proof of work, requiring a clear demonstration of the application of skills and encouraging a “learning-by-doing” approach. Learners progress through role-based pathways that blend foundations, applied modules and even supervised projects. Outputs, which include code, analysis, prompts, agents, write-ups and client-safe simulations, are mapped to a skills framework and checked for meaningful application before EY’s AI Badges are issued. Badges are portable across the whole EY organization and can even stack into EY-funded degree-level pathways (e.g. EY Tech MBA, EY Masters in Business, AI and Data [MBAID]). Results: EY’s AI learning ecosystem is operating at scale and delivering measurable results. In FY25, employees completed 25 million learning hours (average of 61 hours per person) backed by a $442 million in learning investment. The AI Now 2.0 programme, designed for individuals to receive hands-on learning with genAI as their “thought partner”, impacted over 200,000 people, establishing a baseline for safe, effective use. AI depth is global, solid and growing, with more than 100,000 AI Badges awarded, 90,000 in progress, and a broader pool of more than 650,000 EY Badges allocated across the full range of future skills. This proactive and robust learning strategy is expanding AI capabilities and providing leaders verifiable credentials to staff AI projects faster and target coaching where it matters. When benchmarked against industry skills data (from Coursera) for AI/ML, data shows EY is building skills at nearly twice the rate of other enterprises and to a larger extent. For FY25, EY also reported a 30% increase year-on-year in AI-related revenues as these skills were applied into day-to-day work.](https://fws.weforum.org/images/casestudies/aJYTG0000000zzZ4AQ/standard)
