My research examines how digital transformation reshapes jobs, work organisations, and inclusion, combining theoretical modelling with applied policy analysis.
I have successfully designed, led and completed major research projects for a total funded amount of USD 4.0M.
My work contributes to 4 research areas:
I investigate how generative AI reshapes tasks, organisations, and creativity, with a focus on risks, opportunities, and worker–technology complementarities.
Since my PhD, I have advanced research on how technological and organisational innovations impact productivity, work, and inequalities between workers. Building on this foundation, I now lead the FLOW-GenAI initiative (Futures of Labour, Organisation and Work with Generative AI), which investigates how generative AI reshapes tasks, occupations, and creativity at work. My research maps both opportunities and risks of AI adoption, including cybersecurity, misinformation, privacy, and accountability. It emphasises worker–technology complementarities, organisational change, and the societal implications of autonomous systems.
I use innovative research methods by leveraging synthetic data to analyse how GenAI transforms work. I apply task-based methodologies using jobs / occupational classifications like the Australian Skill Classification to measure exposure to AI risks.
Neurodiversity and Work
I pioneered a new research area in economics addressing the intersection of neurodiversity and digital transformation. My publications analyse how assistive technologies, AI, and workplace design can foster inclusion for autistic and neurodivergent workers. This agenda bridges labour economics, innovation, and social inclusion. It has also produced practical tools, including a cost–benefit analysis calculator that allows firms and practitioners to evaluate the benefits of hiring neurodivergent workers. The relevance of this research is underscored by the Australian context, where 40% of NDIS participants access support for autism and, in 2023, 70% of new joiners were diagnosed with autism.
My research on short-time work schemes began in 2006, before the Global Financial Crisis, under a contract with the French Ministry of Labour and Employment. With Oana Calavrezo, I provided the first evidence-based analysis of STW in Europe, using administrative data to evaluate programme efficiency. My recommendations informed regulatory reforms that reduced administrative burdens in 2015 and later extended coverage during COVID-19, underpinning a €35 billion investment that protected employment. This work has been cited in French government reports and presented to the Cabinet of the Prime Minister. More recently, my research examines how STW is evolving to address climate-related shocks. In Australia, I contributed an ex-ante assessment of JobKeeper (2021, Australian Journal of Public Administration) and provided expert advice to the Treasury’s Independent Evaluation of JobKeeper (2023).
I combine quantitative, qualitative, and synthetic data approaches to study transformations in work. My expertise includes panel and cross-sectional analysis, instrumental variables, switching and multilevel models, difference-in-differences, propensity-score matching, PCA, MCA, and cluster analysis. I also develop novel AI-based methods, including synthetic data generation, to map AI risks (cybersecurity, misinformation, privacy, accountability) and workforce exposure. Early in my career, I was instrumental in designing the COI employer–employee survey (Organisational Change and ICT Survey), the first large French dataset on technology, work, and organisation. This survey has become a global reference (over 7,500 citations on Google Scholar) and has underpinned major findings on technology adoption, workplace inequalities, and labour force renewal.