Central banks to explore AI-augmented expertise at IFC workshop
The BIS Irving Fisher Committee (IFC) announced its 5th workshop on Data Science in Central Banking, co-hosted with the Central Bank of the Republic of Türkiye. The event will explore the applications and impacts of artificial intelligence (AI) across central banks' various functions in Istanbul from March 23-25, 2027.
AI's expanding role in central banking
The 5th IFC workshop, co-hosted by the Central Bank of the Republic of Türkiye and supported by the Bank of Italy, will explore the applications and impacts of artificial intelligence (AI) across central banks' diverse functions.
Discussions will address both realized and expected opportunities, as well as challenges concerning efficiency, effectiveness, productivity, quality, and governance.
The event aims to gather practitioners and specialists from central banks, national statistical offices, and international organizations.
A key objective is to highlight ongoing projects and facilitate experience exchange to support in-house expertise, while also assessing the benefits and risks of relying on external AI providers.
Projects with replicable, open-source code are particularly valued.
Seeking practical AI and data solutions
The call for submissions prioritizes applications of AI in central banking, including generative, vision, speech, and language models.
Emphasis is placed on enhancements in productivity, operational efficiency, and knowledge management across policy-making, research, statistics, supervision, and oversight.
Further areas of interest include advanced data science methods for economic analysis and financial stability, as well as technological and data solutions for developing and scaling AI.
Information governance, management, and standards, including the adoption of SDMx and open data technologies, are also key themes.
Accepted contributions will be published in a special issue of the IFC Bulletin.
Beyond hype: Practical AI for central banks
This workshop signifies a crucial step for central banks to move beyond theoretical AI discussions towards practical implementation.
By focusing on real-world applications and governance, it directly addresses the imperative for robust in-house expertise and careful evaluation of external solutions.
The emphasis on replicable code underscores a commitment to tangible, shared progress in integrating AI responsibly.