Calls for regulation from within the artificial intelligence industry mirror a long-standing dilemma in sustainable finance, according to Steve Waygood, chief executive of the Finance Transition Centre. In a commentary for Responsible Investor, Waygood argues that AI leaders urging a slowdown in their own industry's progress echo the financial sector's protracted struggle to confront long-term climate risks.

In September, prominent AI figures — including Dario Amodei of Anthropic, Sam Altman, Demis Hassabis and Elon Musk — voiced concerns about the rapid advancement of AI capabilities. Their intervention 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 displayed by industry insiders raised a pointed question: why would businesses advocate rules that could hinder their own growth?

Waygood's answer lies in the market's inability to price certain risks. In AI, individual firms are incentivized to accelerate development, creating a collective hazard that no single entity can avoid. The finance sector behaves similarly, he says, optimizing for short-term returns while overlooking long-term issues such as climate change.

The financial implications are substantial. A 2022 study estimated the value of stranded fossil-fuel assets — those that lose value prematurely as energy systems realign — in the upstream oil-and-gas sector at $1.4 trillion under a medium realignment scenario. Reinsurer Munich Re reported that natural disasters caused approximately $224 billion in damage in 2025, of which $108 billion was insured; the events also resulted in about 17,200 deaths.

The longer this misalignment persists, Waygood argues, the more abrupt — and potentially destabilizing — the eventual correction will be. A disorderly repricing could produce widespread losses across the financial system that are difficult to contain.

The Finance Sector's Climate Challenge

Waygood draws a direct parallel between the AI industry's self-imposed caution and the finance sector's ongoing difficulty with climate-related risks. Markets, in his view, cannot correct failures inherent in their own incentive structures, and insiders are often the first to recognize and articulate these problems. The Net Zero Asset Managers initiative, a coalition of asset managers, for instance, has acknowledged that its success depended on government policies and regulations.

Mobilizing the estimated $9 trillion annually needed for climate action by 2030 — and more than $10 trillion each year thereafter — requires shifting the incentives that direct private capital. Only governments, Waygood asserts, possess the levers to enact such change, through measures including carbon pricing, standards, procurement andudential rules. The latter dictate the 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 senior coordination and collective buy-in needed to become a top priority. Financial institutions produce extensive climate disclosures, yet these often fail to tell governments which policy changes are necessary or which obstacles stand in the way of transition.

To bridge the 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. These include the necessary carbon prices, product standards, off-take agreements — commitments to purchase future production — and fiscal measures. Aggregating such disclosures, he suggests, could create a roadmap for directing public funds toward the areas where they would attract the most private investment.

He envisions thousands of banks, insurers and companies publicly advocating for the same policy corrections — a coordinated effort that could significantly influence policymaking and provide support for government officials. Such advocacy could foster coalitions and offer reassurance to hesitant ministers. Whether that degree of coordination materializes — and how legislators respond to the AI industry's warnings — will be the near-term markers of whether such insider appeals translate into policy.

Where AI and Climate Intersect

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

Responding to US President Donald Trump's question about why industry leaders would seek 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, he notes, but has historically chosen to navigate around them silently rather than openly acknowledge and address them.

Identifying a hazard, he emphasizes, is distinct from avoiding it. Steering the course remains the government's responsibility, while the finance industry's role is to provide the data and highlight the evident risks.