Unlocking solutions – how AI can transform poverty and inequality
Sep 2025
Enabling world-class research
David Yanagizawa-Drott is an expert in development economics and political economy, focusing on how artificial intelligence (AI) is set to reshape these fields. His research explores how AI can accelerate knowledge production, influence policymaking, and transform economic research. His work spans several pressing topics, including the role of culture and norms in shaping labor markets, the impact of social media and AI on society, and healthcare systems in developing countries.
Pressing challenges to address
- Why do some countries remain trapped in poverty while others prosper?
- What are the most effective ways to integrate AI into economic policymaking to enhance decision-making and governance?
- How can AI be tailored to address the specific needs of the Global South rather than reinforcing existing inequalities?
The persistent gap between the Global North and Global South
Despite decades of research and policy interventions, the economic divide between the Global North and Global South remains vast. Economists have long examined why farmers in low-income countries fail to adopt high-yield seeds, why supply chains for essential medicines break down, and why educational reforms often fall short. While these studies have provided valuable insights, they have yet to fundamentally alter the trajectory of economic development.
Now, AI presents an opportunity to challenge the status quo. Unlike previous technologies, such as vaccines or fertilizers, AI is not a universal tool that can simply be applied across contexts – it must be tailored to local conditions. This requires strong data infrastructure, computational capacity, and local adaptation. The real challenge is not just ensuring AI adoption in developing regions but determining whether it will empower these economies or deepen existing inequalities. Without deliberate efforts, AI may reinforce the divide, concentrating wealth and technological advancements in already developed nations while leaving others behind.
The urgency of this issue is what drives my research. The question of why some countries remain poor while others prosper has fascinated me since my early academic years. While other global challenges, such as curing diseases or solving theoretical problems in physics, may have clear solutions on the horizon, overcoming global poverty remains a daunting and unresolved task. My motivation lies in finding concrete, scalable solutions that can create lasting change.
A new scientific revolution
Over the past fifty years, economics has undergone transformative shifts. What was once a theory-driven discipline evolved with the rise of empirical methods and vast datasets, enabling researchers to test economic hypotheses with unprecedented rigor. Today, AI is poised to trigger another fundamental shift – not just in economics, but across all scientific disciplines.
AI accelerates discovery, reduces research costs, and expands analytical capabilities. It enables researchers to model complex systems, simulate policy impacts, and analyze vast amounts of data at unprecedented speeds. These advancements will likely redefine the field within the next decade, making today’s research methods seem almost unrecognizable.
AI is not merely a tool for more efficient research – it is changing the way knowledge is produced. Machine learning and AI-driven models allow economists to go beyond observational studies, using predictive analytics to anticipate market trends, optimize resource allocation, and design interventions tailored to specific socio-economic conditions.
AI’s potential and the key actors driving change
For AI to serve as a force for economic inclusion rather than exclusion, it must be integrated into key sectors such as healthcare, education, agriculture, and governance. AI-driven diagnostics can help address physician shortages, while predictive models can optimize vaccine distribution and anticipate disease outbreaks. In education, adaptive learning platforms can personalize curricula to bridge learning gaps. AI-powered market insights can help farmers make better agricultural decisions, and machine-learning models can improve tax collection and streamline public administration.
However, AI is not a self-executing solution. Its impact will depend on how it is deployed and who is involved in shaping its use. Three key actors must collaborate to ensure that AI serves inclusive global development rather than reinforcing existing economic divides. First, AI engineers must develop technologies that work within the constraints of developing economies, accounting for limited data availability and infrastructure. Second, economists must identify the systemic inefficiencies and market failures that AI can help resolve, ensuring that technological solutions align with real-world economic challenges. Third, policymakers must create regulatory frameworks that enable AI to benefit the many rather than the privileged few, ensuring that the deployment of AI does not become another tool of economic exclusion.
Without coordinated action among these groups, AI runs the risk of deepening inequalities – benefiting only those who already have the means to integrate and apply it while leaving behind those who need it most.
Zurich’s unique position in advancing AI and economic research
Zurich is uniquely positioned to lead the global effort to harness AI for economic development. As a hub for cutting-edge research in behavioral economics, development policy, and technology, the city brings together some of the world’s leading institutions, including the University of Zurich and ETH Zurich. These institutions foster interdisciplinary collaboration, enabling researchers to explore how technology can be harnessed for global economic inclusion.
I was drawn to Zurich for these very reasons. Having spent time at Harvard, I saw the potential for Zurich to emerge as a leading center for economic research, thanks to the UBS Center’s ability to attract top scholars and provide the resources needed for ambitious projects. Beyond academic appeal, the city offered a unique balance between a thriving intellectual environment and a high quality of life, ultimately influencing my decision to relocate.
The road ahead
The integration of AI into economics and policymaking will not be immediate, nor will it be without challenges. Developing machine-learning models that can function effectively in low-resource environments requires time, investment, and collaboration. Many regions still lack the digital infrastructure needed to support AI-driven solutions, and adapting algorithms to diverse economic conditions is a complex task.
Yet, the potential is too significant to ignore. If AI is harnessed effectively, it could unlock solutions to poverty and inequality that have eluded researchers for decades. However, success will depend on an active, coordinated effort between researchers, engineers, and policymakers to ensure that AI is designed and deployed with inclusivity at its core.
As we move forward, one thing is certain: AI will reshape economic research and policymaking. The question is no longer whether AI will transform the field – it already is. The real challenge lies in ensuring that this transformation benefits all rather than widening the gap between those who have access to cutting-edge technology and those who do not.
David Yanagizawa-Drott is an expert in development economics and political economy, focusing on how artificial intelligence (AI) is set to reshape these fields. His research explores how AI can accelerate knowledge production, influence policymaking, and transform economic research. His work spans several pressing topics, including the role of culture and norms in shaping labor markets, the impact of social media and AI on society, and healthcare systems in developing countries.
Pressing challenges to address
- Why do some countries remain trapped in poverty while others prosper?
- What are the most effective ways to integrate AI into economic policymaking to enhance decision-making and governance?
- How can AI be tailored to address the specific needs of the Global South rather than reinforcing existing inequalities?
The persistent gap between the Global North and Global South
Despite decades of research and policy interventions, the economic divide between the Global North and Global South remains vast. Economists have long examined why farmers in low-income countries fail to adopt high-yield seeds, why supply chains for essential medicines break down, and why educational reforms often fall short. While these studies have provided valuable insights, they have yet to fundamentally alter the trajectory of economic development.
Now, AI presents an opportunity to challenge the status quo. Unlike previous technologies, such as vaccines or fertilizers, AI is not a universal tool that can simply be applied across contexts – it must be tailored to local conditions. This requires strong data infrastructure, computational capacity, and local adaptation. The real challenge is not just ensuring AI adoption in developing regions but determining whether it will empower these economies or deepen existing inequalities. Without deliberate efforts, AI may reinforce the divide, concentrating wealth and technological advancements in already developed nations while leaving others behind.
David Yanagizawa-Drott is a Professor of Development and Emerging Markets in the Department of Economics at the University of Zurich and an Affiliated Professor at the UBS Center.
Quotes
The real challenge is not just ensuring AI adoption in developing regions but determining whether it will empower these economies or deepen existing inequalities.
AI will reshape economic research and policymaking.
Economic challenges of our time
From rising inequality and global trade tensions to climate change and the impact of artificial intelligence on labor markets – economists today are grappling with fundamental questions that will shape our collective future. In this special edition of the Public Paper series, all affiliated professors of the UBS Center share their perspectives on these challenges. Their contributions highlight how cutting-edge research conducted at the Department of Economics at the University of Zurich can help us better understand – and potentially solve – some of the most urgent issues of our time.
It is precisely this ambition that defines the UBS Center for Economics in Society. Since its founding, the Center has served as a platform for dialogue between academia, business, and policymakers and as a catalyst for excellence in economic research. That vision goes back to Kaspar Villiger. As the founding Chairman of the Foundation Council, he played a pivotal role in establishing and shaping the UBS Center.
With this fifteenth edition of the Public Paper series, we honor Kaspar Villiger’s extraordinary contributions and legacy. By strengthening research capacity at the University of Zurich and fostering public dialogue around key societal questions, his vision continues to inspire the Center’s mission: bridging knowledge and society to build a better future.
From rising inequality and global trade tensions to climate change and the impact of artificial intelligence on labor markets – economists today are grappling with fundamental questions that will shape our collective future. In this special edition of the Public Paper series, all affiliated professors of the UBS Center share their perspectives on these challenges. Their contributions highlight how cutting-edge research conducted at the Department of Economics at the University of Zurich can help us better understand – and potentially solve – some of the most urgent issues of our time.
It is precisely this ambition that defines the UBS Center for Economics in Society. Since its founding, the Center has served as a platform for dialogue between academia, business, and policymakers and as a catalyst for excellence in economic research. That vision goes back to Kaspar Villiger. As the founding Chairman of the Foundation Council, he played a pivotal role in establishing and shaping the UBS Center.
David Yanagizawa-Drott on Google Scholarbrowse
Author
Professor of Development and Emerging Markets, Affiliated Professor at the UBS Center
David Yanagizawa-Drott received his PhD from IIES at Stockholm University in 2010. At that point, he was hired as Assistant Professor at John F. Kennedy School of Government, Harvard University. He was then promoted to Associate Professor in 2014. In 2016, he was hired as a full professor at University of Zürich. His research has shown that propaganda can cause violent conflict, studying the impact of hate media during the Rwanda Genocide. David has also examined the role of political protests in shaping policy outcomes and elections, establishing evidence that they can be highly effective in moving public opinion. In developing countries, a lot of his work focuses on the how to improve health outcomes and economic outcomes for poor households. In this line of work, for example, David implemented a randomized field experiment that showed that a simple Community Health Worker intervention in Uganda, based on a social entrepreneurship model, reduced child mortality by more than twenty percent. David is a member of several research networks, such as Poverty Action Lab (J-PAL), The Bureau for Research and Economic Analysis of Development (BREAD), European Development Research Network (EUDN) and Center for Economic Policy Research (CEPR). His work has been highlighted in various international media outlets, such as the New York Times, Washington Post, The Guardian, The Economist and various national TV news broadcasts in the U.S.
Professor of Development and Emerging Markets, Affiliated Professor at the UBS Center
David Yanagizawa-Drott received his PhD from IIES at Stockholm University in 2010. At that point, he was hired as Assistant Professor at John F. Kennedy School of Government, Harvard University. He was then promoted to Associate Professor in 2014. In 2016, he was hired as a full professor at University of Zürich. His research has shown that propaganda can cause violent conflict, studying the impact of hate media during the Rwanda Genocide. David has also examined the role of political protests in shaping policy outcomes and elections, establishing evidence that they can be highly effective in moving public opinion. In developing countries, a lot of his work focuses on the how to improve health outcomes and economic outcomes for poor households. In this line of work, for example, David implemented a randomized field experiment that showed that a simple Community Health Worker intervention in Uganda, based on a social entrepreneurship model, reduced child mortality by more than twenty percent. David is a member of several research networks, such as Poverty Action Lab (J-PAL), The Bureau for Research and Economic Analysis of Development (BREAD), European Development Research Network (EUDN) and Center for Economic Policy Research (CEPR). His work has been highlighted in various international media outlets, such as the New York Times, Washington Post, The Guardian, The Economist and various national TV news broadcasts in the U.S.