As artificial intelligence technology enters a period of rapid iteration, the operating logic and risk structure of global financial markets are undergoing profound changes. Central banks and financial regulatory agencies in many European countries have collectively warned that the development speed of artificial intelligence has far exceeded the pace of updating traditional financial regulations and policies, and is continuously challenging the existing monetary policy framework and financial stability system.

European policymakers are currently facing a dilemma: they need to leverage AI technology to boost economic productivity and revitalize financial markets, while simultaneously taking all necessary precautions against emerging technological risks and safeguarding the stability of financial markets.

Differences in the financial systems of Europe and the United States have widened the divergence in AI development.

From the perspective of the global financial landscape, the industrialization of AI has become a key factor influencing the divergence between strong and weak capital markets.

Market investors generally believe that the continued increase in investment in the AI industry is one of the core drivers of the long-term strength of the US stock market.

In contrast, the European market, relying on the traditional financial system dominated by banks, has relatively narrow financing channels for AI technology companies in the region . The progress of technology research and development and industrial application lags behind that of the United States, which also makes European monetary policy face more constraints in adapting to the development of the new AI track.

Traditional regulatory models have failed, prompting the UK to pioneer a new governance system for AI.

Against the backdrop of rapid technological innovation, the adaptability of Europe's traditional financial regulatory system continues to decline. Policymakers urgently need to restructure their regulatory and monetary policy thinking and find the optimal balance between promoting the application of AI technology and preventing financial risks.

Nicky Lassie, Chief Executive of the UK Financial Conduct Authority, stated that with the rapid popularization of cutting-edge technologies such as autonomous AI, the traditional, fixed-cycle regulatory rule-making model has become ineffective and is completely unable to keep up with the rapid iteration pace of the current technology industry, which takes weeks or months to complete.

In an interview, Lassie further pointed out that innovations in the field of artificial intelligence are emerging one after another, and regulators must break out of their conventional thinking and abandon rigid regulatory models. The UK has already taken the lead, relying on the Financial Stability Board to conduct specialized research on cutting-edge AI regulation, and has also established an AI Security Institute to help regulators and policymakers understand the risk logic of AI financial applications, providing support for the precise implementation of monetary and regulatory policies, and promoting the safe and compliant application of AI technology in the financial market.

The ECB sets the tone: AI presents both growth opportunities and systemic risks.

The European Central Bank (ECB) also attaches great importance to the profound impact of AI on monetary policy and financial stability. ECB President Christine Lagarde stated in an interview that artificial intelligence is a crucial tool for improving overall societal productivity and empowering economic growth, and it has positive significance for Europe's economic recovery and industrial upgrading. However, at the same time, the new risks brought about by this technology are far greater than traditional financial risks, posing a completely new challenge to European monetary policy regulation.

Lagarde analyzed that over the past decade, the European Central Bank's policy risk control focus has been on conventional financial security issues such as cyberattacks, data breaches, and hacking. However, with the continuous upgrading of AI models and the comprehensive expansion of application scenarios, the speed, scope, and complexity of financial market risks have increased significantly.

Currently, the global defense system against AI financial risks is not yet perfect, and there is a serious lack of supporting risk control funds and response mechanisms, which significantly increases the difficulty for the European Central Bank in formulating monetary policies and predicting risks.

At the European Central Bank's annual forum held this week in Sintra, Portugal, the impact of AI on productivity, market fairness, and monetary policy became a core topic. This high-profile summit, comparable to the Jackson Hole global central bank symposium, highlighted the European policymakers' vigilance regarding the risks of AI and emphasized that AI has become a key variable influencing adjustments to European monetary and financial policies.

AI may amplify market volatility; central bank proposes a "circuit breaker" risk control solution.

At the forum, Bank of England Deputy Governor Sarah Briden specifically warned of the amplifying effect of AI on financial market volatility, a risk that could directly interfere with the effectiveness of monetary policy.

She stated that currently, financial institutions are only applying their proprietary AI to low-risk, routine business such as market research, resulting in a limited impact on the market. However, the industry's application landscape could change drastically at any time. Once AI is fully and deeply involved in financial transactions, during periods of market pressure and tightening liquidity, the concentrated operation of intelligent AI could easily amplify market volatility and trigger systemic market fluctuations.

In response, Briden proposed a new approach to regulatory risk control, suggesting the establishment of a dedicated protection mechanism for AI financial applications. He recommended drawing on the risk control logic of stock market circuit breakers and emergency trading shutdowns to set up "circuit breakers" for AI transactions.

When AI model failures or algorithmic deviations cause abnormal market fluctuations, all related transactions can be restricted or suspended in a timely manner to block the transmission of risks and ensure a stable market environment for monetary policy regulation.

Europe's AI development lags behind, and there are shortcomings in the transmission of policy benefits.

In addition to the pressure of risk control, European monetary policy reform also faces the practical dilemma of lagging technological development.

European Central Bank Vice President Boris Vujicic admitted that Europe has fallen behind the world's leading level in cutting-edge AI technology research and development and the cultivation of science and technology innovation enterprises . At present, it is urgent to build an independent and controllable AI technology system and strengthen technological sovereignty.

Europe has always had the ability to adapt and implement new technologies and boost production efficiency through technology, but it has consistently failed to stand at the forefront of global technological innovation. This has also resulted in European monetary policy failing to adapt to the development dividends of the AI industry in a timely manner, and the policy empowerment effect falling short of market expectations.

Future policy tone: a balance between inclusive innovation and strict risk control

Regarding the future direction of regulatory and monetary policy adjustments, Lassie provided a clear direction. He emphasized that policymakers will not impose blanket restrictions on the financial application of AI technology to avoid hindering technological innovation and economic growth, but they must not expose the financial market to unknown AI risks that are unmonitorable and unpredictable.

This means that European monetary policy and financial regulation will undergo a comprehensive reform, moving away from the traditional cyclical rule update model and implementing precise policies to address new types of financial crimes and market volatility risks caused by AI through innovative regulatory tools and the establishment of government-enterprise collaboration mechanisms.

While safeguarding the compliant development of AI and helping to improve the quality and efficiency of the economy, we must uphold the bottom line of market fairness and financial stability, and achieve a two-way balance between technological innovation and monetary and financial stability.