Beau: AI poses challenges for central bank policy and sovereignty
Denis Beau, First Deputy Governor of the Banque de France, outlined the significant challenges posed by artificial intelligence for central bank objectives and internal operations in a speech on April 2, 2026. He emphasized impacts on monetary and financial stability, alongside critical sovereignty concerns.
AI's dual impact on stability mandates
The Banque de France monitors AI's economic impact for price stability, noting its substantial immediate effect on investment in US semiconductor and software sectors and French data centers.
Long-term, AI is projected to significantly boost productivity, potentially increasing global growth by 0.1 to 0.4 percentage points annually.
However, AI's overall impact on inflation and the nominal interest rate (r*) remains highly uncertain due to its complex effects on supply and demand, meaning no clear conclusions for monetary policy can yet be drawn.
For financial stability, AI's widespread adoption by financial intermediaries presents new risks, particularly institutions' reliance on major AI model and cloud service providers.
An ACPR survey shows nearly all French banks and insurers use AI, necessitating robust regulatory oversight.
Supervisors must develop capabilities and methodologies for assessing AI systems, focusing on explainability and fairness, to ensure controlled development and mitigate these emerging risks.
Internal transformation and SupTech innovation
AI is an operational tool integral to the Banque de France's daily work, supported by a robust data platform and in-house expertise.
The Bank deployed Copilot Chat across all workstations in 2025, introducing staff to AI's potential within a secure framework.
To accelerate adoption, the "Innovative Bank" initiative, launched in February 2026, focuses on clear AI governance, process automation, and making AI accessible to all employees, aiming to boost productivity.
A key innovation is the SupTech tool 'Véridic', an LLM developed by the ACPR.
It classifies life insurance products by complexity and risk, enhancing supervisory efficiency.
Lessons from AI deployment highlight simplifying concepts before automation and training staff in both tool usage and risk awareness.
Autonomy at stake
The adoption of AI by central banks presents a profound challenge to their autonomy, especially when handling sensitive financial data.
Over-reliance on non-European technology components creates significant risks, including supplier dependency and the potential loss of control over critical systems.
Central banks must prioritize data sovereignty and technological resilience, ensuring innovation never compromises their fundamental mission.