In Europe—especially in Luxembourg—the green and digital transitions demand a workforce equipped with the right skills. But what strategic investments are needed to ensure workers, firms, and institutions can drive technological change and sustain long-term prosperity?

To bridge the gap between technological progress and workforce readiness, we produce state-of-the-art research as well as innovative metrics that track labor market trends and inform forward-looking policies. To achieve this, we collaborate with key stakeholders—ministries, training centers, and the private sector—and use a variety of methodologies.

First, we leverage big data, combining firm-level web-scraped information, surveys, and official registers to map AI adoption patterns across multiple European countries. This approach not only highlights cross-country differences in technology uptake but also uncovers key organizational challenges, such as internal restructuring needs and skill gaps. By training machine learning models on firm data, we can predict which companies are most likely to adopt AI and how this impacts productivity, workforce transformation, and broader industry shifts.

Second, we conduct randomized controlled trials (RCTs) to assess the impact of targeted interventions on workers, job seekers, and firms. These include personalized skill development suggestions, role-model testimonials, and financial incentives. By identifying and addressing barriers to reskilling and upskilling, we generate evidence-based insights to refine training programs and craft more effective policy recommendations.

Together, these two approaches provide a comprehensive perspective on workforce transformation. While big data analysis identifies structural trends, predicts AI adoption, and maps emerging skill demands, RCTs focus on individual and organizational behavior, revealing how different interventions can effectively motivate and support workers and firms in adapting to change. By combining these methods, we not only diagnose skill gaps and organizational barriers but also test concrete solutions, ensuring that our policy recommendations are both data-driven and empirically validated.