Ludovic Di Biaggio, Professor of Economics and Researcher at SKEMA Business School, is particularly interested in the conditions and factors that foster innovation, as well as its effects on organisations and territories in industrial contexts linked to semiconductors, biotechnologies, fuel cells and artificial intelligence. He tells us more about his work on AI, what surprised him the most and how his research is impacting society.
Could you tell us more about your field of research, particularly your research on Artificial Intelligence?
My interests in questions related to AI on economy, business, and society in general are quite broad. I had the chance to coordinate OTESIA (the Observatory of the Technological, Economic and Social Impacts of Artificial Intelligence) for two years. It gave me the opportunity to discuss with managers, policy makers and scientific experts from different fields. Ethical issues raise major concerns, and I had the opportunity to attend several roundtables, meetings and workshops organized by the UNESCO Chair in the Ethics of the Living and the Artificial. I am fascinated to see how digital technologies, and AI more specifically, raise questions that actually are opportunities to challenge and rediscuss the foundation and the resilience of our democratic societies.
But my main contribution is probably the first report “AI: Technologies and Key Players” written with my colleague Lionel Nesta and our data scientist Mohamed Keita. This report highlights the strategic challenges that nations must confront to sustain their competitiveness and, more broadly, to preserve their economic independence. Navigating these challenges requires difficult decisions, given that AI is not just a single technology but a system encompassing various technologies, all of which are still in their early stages of development. In addition, AI has many applications across various industries, making strategic investment allocation decisions risky, but also crucial. Currently, European and Asian countries trail behind the US, emphasising the importance of selecting technologies tailored to specific sectors in order to establish a strategic positioning.
What results surprised you the most?
I think the most surprising observation in the report is the specificity of national innovations systems. Science plays a pivotal role in the advancement of AI technology, and the interaction between public and private institutions is interesting to analyse. Despite similar or close strategic plans, the role of public research institutions and private corporations varies significantly across countries. We examined the collaborative structures between public and private institutions and discovered significant variations in the contributions of public and private institutions to AI-related innovations. Moreover, we observed differences in the inclination of corporate researchers to collaborate with public scientists, with country-specific patterns, suggesting different research and development traditions. Finally, the level of openness to international collaborations is notably different across countries. In a chapter published in L’économie française 2024 (OFCE “Repères” Collection), we show that French public institutions play a dominant role in France while private corporations are much less active than in other countries such as Germany or Japan. They collaborate much more than their international counterparts, but very little with private companies compared to other companies, and they have much less international exposure.
What is the research you are currently carrying out?
With Iris Poon, a PhD student, we try to understand how the adoption of AI is transforming industries, reshaping the organization of value chains. As many industries, the automobile industry, is experiencing a series of disruptive trends related to the combination of electrification, autonomous or semi-autonomous driving, connectivity, and shared mobility, compelling a consequential “Artificial intelligence (AI) imperative.” This gives us an opportunity to analyse how technological disruptions affect products design, change vertical and horizontal divisions of labour, and question the role and power of leading actors.
Can it be interesting to companies from other industries?
Automakers are not the only ones facing this AI imperative. AI lies at the heart of ‘Software Defined’ products, a new class of products where the software is the focus and adds more value than the hardware. TESLA, for example, built on the capability to transform a vehicle into a system that is constantly connected to its environment, and can continuously evolve with the integration of new applications and functions uploaded throughout the car’s lifespan. We observe a similar evolution in various sectors, such as the telecommunications industry with the implementation of software-defined networking (SDN). The question is whether these industries will undergo dynamics like those witnessed in the PC industry during the eighties. Will we witness new specialist entrants driving vertical disintegration and a gradual decline in the influence of established leaders? Our intuition suggests that the narrative may not be identical for major automakers. We want to investigate why.