A recent survey highlights a significant disparity between the speed at which financial institutions are integrating artificial intelligence (AI) and the capabilities of regulatory bodies to oversee these developments. The findings, released by the Cambridge Centre for Alternative Finance, reveal that central banks and financial regulators are falling behind in AI adoption, potentially jeopardising their ability to manage emerging risks effectively.
Regulatory Blind Spot in AI Adoption
The report underscores a troubling trend: financial firms are embracing AI technologies at more than double the pace of their regulatory counterparts. Only 20% of the regulators surveyed indicated they have achieved “advanced AI adoption.” Meanwhile, a mere 24% of these authorities collect relevant data on AI integration within the industry, with 43% having no plans to begin such data collection in the next two years.
“This empirical blind spot may undermine the prevailing optimism surrounding AI,” the report cautions. “Authorities cannot successfully harness or oversee AI if they are navigating its adoption and risks without solid data.”
The research, conducted in collaboration with the Bank for International Settlements, the International Monetary Fund, and various multilateral institutions, involved input from 350 traditional financial institutions and fintech firms, over 140 AI vendors, and 130 central banks and regulatory authorities across 151 countries.
Rising Risks from Advanced AI Models
As AI technology evolves, so do the complexities and risks associated with it. The release of Anthropic’s Mythos has been particularly alarming for cybersecurity experts, who warn that such models could pose significant challenges to the banking sector and its outdated technology infrastructures. This latest generation of AI systems may have the capability to exploit software vulnerabilities, thereby undermining existing governance and oversight mechanisms.
Regulators have engaged with financial institutions to assess the preparedness of their legacy systems for these advanced AI models. The report identifies Mythos as a prime example of a system that could create substantial operational risks for banks if not managed correctly.
“The principle that financial firms should remain accountable for harms, including cyberattacks, regardless of whether AI is developed in-house or by third-party vendors, becomes increasingly difficult to uphold with the advent of more autonomous systems,” the authors noted.
The Need for Enhanced Regulatory Frameworks
The report advocates for a shift in regulatory approaches, urging authorities to develop their own capabilities in AI to effectively oversee the systems they regulate. Harish Natarajan, a practice manager for competitiveness and innovation at the World Bank, pointed out during the report’s launch that many authorities in emerging economies lack both the data and the necessary skills to implement AI solutions effectively.
Furthermore, the survey raises alarms about the financial sector’s growing reliance on a select few powerful AI providers. It found that 69% of respondents depend on OpenAI, with that figure climbing to 76% among financial industry participants. This concentration creates a “notable critical third-party risk consideration,” exposing the global financial system to potential vulnerabilities, pricing shocks, or supply disruptions.
An Urgent Call for Data-Driven Governance
At the time of the survey, which took place between October 2025 and January 2026, over half of the respondents reported using Google’s AI models, while slightly more than a third were utilising Anthropic’s offerings. The findings clearly indicate an urgent need for regulators to not only catch up with the rapid advancements in AI but also to establish robust frameworks that ensure accountability and oversight in a landscape increasingly dominated by autonomous systems.
Why it Matters
The implications of this gap in AI adoption and oversight are profound. As financial institutions continue to integrate powerful AI technologies, the risks associated with cyber threats and operational vulnerabilities will rise. Without a strong regulatory framework backed by comprehensive data, the financial system may face unprecedented challenges, potentially jeopardising economic stability on a global scale. As such, it is imperative for regulators to enhance their capabilities and adapt to the evolving landscape of AI in finance to safeguard the integrity of the financial ecosystem.
