Calls for regulation within the artificial intelligence industry mirror a long-standing challenge in sustainable finance, according to Steve Waygood, chief executive of the Finance Transition Centre. Leaders in AI have publicly urged for a slowdown in their industry’s progress, a move Waygood compares to the financial sector’s struggle to address long-term climate risks.

In September, AI leaders, including Dario Amodei of Anthropic, Sam Altman, Demis Hassabis, and Elon Musk, expressed concerns about the rapid advancement of AI capabilities. This coincided with legislative efforts, such as a bill introduced by Senator Bernie Sanders and Representative Greg Casar, to ban the development of artificial superintelligence. The urgency from industry insiders prompted questions about why businesses would advocate for regulations that could potentially hinder their growth.

Waygood suggests that these calls stem from an inability of the market to price in certain risks. In AI, individual firms are incentivized to accelerate development, creating a collective hazard that no single entity can avoid. Similarly, the finance sector optimizes for short-term returns, often overlooking long-term issues like climate change. The financial implications of climate change, such as stranded fossil-fuel assets, are estimated to be $1.4 trillion in the upstream oil-and-gas sector under a medium realignment scenario, according to a 2022 study.

Natural disasters caused approximately $224 billion in damage in 2025, with $108 billion of that being insured, Munich Re reported. These events also resulted in about 17,200 deaths. Waygood argues that the longer this misalignment persists, the more abrupt and potentially destabilizing the correction will be. A disorderly repricing could lead to widespread financial system losses that are difficult to contain.

The Finance Sector’s Climate Challenge

Waygood draws a parallel between the AI industry’s self-imposed caution and the finance sector’s ongoing challenge with climate-related risks. He states that markets are unable to correct failures inherent in their own incentive structures, and insiders are often the first to recognize and articulate these issues. The Net Zero Asset Managers initiative, for instance, acknowledged that its success depended on government policies and regulations.

Mobilizing the estimated $9 trillion annually needed by 2030 for climate action, and over $10 trillion thereafter, requires shifting the incentives that direct private capital. Waygood asserts that only governments possess the levers to enact such change through measures like carbon pricing, standards, procurement, and prudential rules. These rules dictate capital reserves banks must hold against risks that may not yet be apparent on their balance sheets.

Unlike the AI industry, which has clearly communicated its concerns and desires to legislators, the finance sector has not presented a unified front. Waygood believes the issue has lacked the necessary senior coordination and collective buy-in to become a top priority. While financial institutions produce extensive climate disclosures, these often fail to inform governments about necessary policy changes or identify obstacles to transition.

To bridge this gap, Waygood proposes that companies and financial institutions disclose not only their emissions but also the specific policy measures that would enable a credible transition pathway in their respective sectors. This includes identifying necessary carbon prices, product standards, off-take agreements, and fiscal measures. Aggregating these disclosures could create a roadmap for directing public funds to attract the most private investment.

Waygood envisions thousands of banks, insurers, and companies publicly advocating for the same policy corrections, which could significantly influence policymaking and provide support for government officials. The potential for such coordinated advocacy could foster coalitions and offer reassurance to hesitant ministers.

The connection between AI and climate action is also tangible. The data centers powering AI development are increasing electricity demand, yet AI technology itself could enhance climate forecasting, balance power systems, and accelerate climate science research. Ultimately, whether AI becomes a climate burden or a tool for good will depend on the incentives established around it, which Waygood frames as a governance issue rather than a purely engineering one.

Addressing Trump’s question about industry leaders seeking regulation, Waygood concludes that such calls arise when market participants recognize they are heading toward danger and cannot alter course alone. The finance industry has long been aware of its climate-related risks but has historically chosen to navigate around them silently rather than openly acknowledge and address them. He emphasizes that identifying a hazard is distinct from avoiding it, and steering the course remains the government’s responsibility, while the finance industry’s role is to provide the data and highlight the evident risks.