The value of codifying organisational knowledge

About the seminar topic

Mature organisations are more productive largely because of knowledge accumulated through experience. Most of it remains tacit, so new organisations cannot easily learn it from their predecessors. Artificial intelligence can codify such knowledge without humans articulating it. How much is at stake? We define the value of codifying organisational knowledge as the output gain when new organisations are ‘born old’, drawing their initial knowledge from the distribution of mature ones. In a class of knowledge-based models of firm dynamics, this value depends on 2 statistics from observed firm life cycles: the relative size and lifespan of mature firms. A modest AI system learning from successive cohorts can achieve this. US data suggests a potential gain of up to one Gross Domestic Product (GDP), implying that AI could have a meaningful macroeconomic impact by codifying organisational knowledge alone, even if it automated neither production nor innovation. Across industries, the value of codification varies widely and complements existing measures of AI exposure.

Speaker bio

Eduard Talamàs is an Associate Professor of Economics at IESE Business School, University of Navarra, in Barcelona. He studies the impact of artificial intelligence on the knowledge economy. His work on this topic has appeared in the Journal of Political Economy and other top economics journals.

Eduard regularly presents his research at top research departments, conferences, policy institutions and AI labs. He is a Digital Fellow at the Stanford Digital Economy Lab, a Research Affiliate at the Centre for Economic Policy Research and a Research Fellow at the Barcelona School of Economics (BSE). His research is also supported by Google through its inaugural AI & Economy Researchers Program.

In 2025, Eduard co-authored Transformative AI and Firms, with Aaron Chatterji and Daniel Rock, a research agenda chapter in the National Bureau of Economic Research (NBER) volume The Economics of Transformative AI. Since then, he organises the Economics of Transformative AI workshop at the BSE Summer Forum and teaches a second-year MBA elective on this topic at IESE Business School.

Eduard received his PhD in economics from Harvard University in 2017 and subsequently was a postdoctoral fellow at the University of Pennsylvania’s Warren Center for Network and Data Sciences. He was named one of Poets&Quants’ World’s Best 40-Under-40 MBA Professors in 2022.

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