A new survey from the Official Monetary and Financial Institutions Forum (OMFIF) shows that central banks around the world remain cautious about integrating artificial intelligence (AI) into essential operations. Despite growing interest in digital tools, officials still prefer traditional systems, especially when dealing with monetary policy and financial stability. The report, released this week, also reveals that central banks continue to rely heavily on the US dollar, with limited movement toward alternative currencies or digital-asset reserves.

🧠 Limited Confidence in AI for Critical Decisions

According to the survey, many central banks view AI as promising for data analysis, fraud detection and workflow automation. However, few are ready to use it for core decision-making. Respondents expressed concerns about transparency, reliability and cybersecurity. These worries have slowed adoption in areas like interest-rate modelling, economic forecasting and regulatory oversight.

Several officials noted that AI models can behave unpredictably when exposed to incomplete or biased data. Due to these risks, most institutions prefer using AI as a support tool, rather than replacing human judgment. This cautious approach mirrors earlier patterns seen during the introduction of blockchain and algorithmic-trading technologies.

💵 Global Reliance on the Dollar Remains Strong

The survey found that despite new discussions on monetary diversification, the US dollar remains the dominant currency in global reserves. Central banks reported only minimal shifts toward digital currencies or alternative reserve assets. Even in regions exploring central-bank digital currencies (CBDCs), confidence in the dollar’s stability continues to guide long-term reserve planning.

Analysts suggest that geopolitical uncertainty, volatile commodity markets and uneven digital-currency regulations have reinforced the dollar’s appeal. Many banks view it as a reliable anchor during periods of economic pressure.

🔍 Digital Tools Growing — but Slowly

Central banks are adopting new tools in limited, targeted ways. For example, many institutions now use machine-learning models to detect abnormal transaction patterns and support anti-fraud systems. Others apply AI to enhance internal risk assessments. However, widespread transformation of monetary operations remains distant.

The report also notes that interest in digital finance—such as tokenisation and CBDCs—continues to rise. Yet, most central banks prefer to take gradual steps, focusing on pilot projects and consultative studies.

🌐 What This Means for the Financial World

As global markets navigate new technological shifts, the survey suggests that monetary authorities are prioritising stability over rapid innovation. Their cautious stance highlights the complexity of integrating AI into highly sensitive financial systems. For investors and policymakers, the findings signal that the global financial architecture will likely evolve slowly, with digital tools playing a supporting rather than central role in the near future.