The Bank of International Settlements (BIS) has said that the rapid adoption of artificial intelligence (AI) requires central banks to embrace the new technology.

It’s also urging policymakers to anticipate the effects of AI on the economy, and use it to sharpen their own analytic tools in pursuit of financial and price stability.

In a special chapter of its new BIS Annual Economic Report, it’s laid out the implications of new AI applications for central banks.

AI is poised to impact the financial system, labour markets, productivity, and economic growth.

With widespread adoption, AI could enhance firms’ ability to adjust prices faster in response to macro-economic changes with repercussions for inflation dynamics.

The jobs of central backs as stewards of the economy will also be directly affected as frontline users of AI tools.

Central bank uses cases for AI include enhancing nowcasting by using real-time data to better predict inflation and other economic variables, and to sift through data for financial system vulnerabilities.

Data has become an even more valuable resource with the advent of AI, and will be the cornerstone of central banks’ use of the technology, also said BIS.

In the financial sector, AI can also improve efficiencies and lower costs for payments, lending, insurance and asset management, the report outlined.

However, BIS cautioned that AI also introduces risks, such as new types of cyber-attacks, and may amplify existing ones—such as herding, runs, and fire sales.

Hyun Song Shin, head of research and economic adviser at the BIS, said: “New generation AI models have captured our collective imagination through their uncanny abilities, but they also have a direct bearing on how central banks do their jobs.

“Vast amounts of data could provide us with faster and richer information to detect patterns and latent risks in the economy and financial system.

“All this could help central banks predict and steer the economy better.”

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Cecilia Skingsley, head of the BIS Innovation Hub—which is testing AI’s capabilities in several areas together with central bank partners—further added: “Central banks were early adopters of machine learning and are therefore well positioned to make the most of AI’s ability to impose structure on vast troves of unstructured data.”