Gary Gensler, the Chairman of the United States (US) Securities and Exchange Commission (SEC), maintains a watchful eye on the role of Artificial Intelligence (AI) in the financial landscape.

His recent warnings serve as a cautionary note for regulators, underlining the need to remain vigilant regarding AI's pervasive influence.

Gary's message is clear: taking proactive measures is imperative to mitigate the potential for financial instability in the coming decade.

The heart of his concerns lies in the ever-increasing concentration of data managed by AI-driven platforms, which he identifies as a burgeoning risk to the stability of financial systems.

While he firmly advocates for regulation, he acknowledges the monumental challenge of crafting a comprehensive AI framework for the US.

Gary admits it is a tough challenge:

“It's frankly a hard challenge. It's a hard financial stability issue to address because most of our regulation is about individual institutions, individual banks, individual money market funds, individual brokers; it's just in the nature of what we do. And this is about a horizontal [matter whereby] many institutions might be relying on the same underlying base model or underlying data aggregator.”

The multitude of innovative solutions emerging from tech firms often diverges from the precise role of the SEC, introducing complexity into the regulatory landscape.

Gary Gensler's All For Full AI Regulation

It is important to note that the SEC, under Gary's leadership, has not remained idle on the matter of AI regulation.

He has consistently emphasised the SEC's commitment to endorsing positive AI developments, actively soliciting support from Congress to reinforce this stance.

The advent of commercialised AI products, exemplified by OpenAI's ChatGPT and subsequent innovations such as Google's Bard, has expanded the capabilities of AI systems.

These technologies now generate diverse and sophisticated responses from basic prompts.

However, as Gary grapples with taming AI, it remains a complex endeavour, considering the evolving nature of its applications across various industries.

One aspect is abundantly clear: addressing conflicts of interest within AI-modelled financial data is only a partial solution.