Business Is Facing Up to the Risks of Destroying the Natural World

Hundreds of businesses have volunteered to measure and report their impact on the natural world, as they recognise the growing risks to their own operations from environmental degradation, including a denuded Amazon rainforest and dying coral reefs.

While many businesses are struggling to meet coming requirements to report their climate impact, more than 300 banks and companies are pledging to go much further. Early movers from across sectors and countries have promised to regularly publish nature-impact information as set out by the Taskforce on Nature-Related Financial Disclosures, or TNFD, a United Nations-backed initiative.

The first adopters represent $4 trillion in market capitalisation and around $14 trillion in assets under management. They include seven of the world’s 29 globally systemic banks, Japanese investor SoftBank, Norway’s sovereign-wealth fund, Gucci parent Kering, miner Anglo American and pharmaceutical majors GSK, AstraZeneca and Novo Nordisk.

Take-up by sector leaders should encourage peers to accelerate their efforts, said Tony Goldner, executive director of the TNFD. The framework is aligned to the Kunming-Montreal Global Biodiversity Framework agreed to in 2022 by nearly 200 countries. It recommends disclosures in governance, strategy, risk and impact management, as well as sector-specific metrics and targets for reducing impact.

Biodiversity impact is both a new type of risk and a new opportunity, said Valentin Alfaya, sustainability director at Spanish-listed infrastructure group Ferrovial, one of the first movers. “As a consequence of the implementation of the TNFD and our own natural capital assessment program, sometimes investments are going to be left aside,” Alfaya said.

“When you are interacting with those protected areas that are very relevant in terms of ecological value…it’s really risky for the company, not just in terms of reputation but also in terms of operations and even finance,” he said.

Using the framework will guide investment and help integrate nature into financial decision making, said Marisa Drew, chief sustainability officer at lender Standard Chartered. The move is a “significant opportunity for us to facilitate financial flows toward nature-positive outcomes,” Drew said.

Gauging impact is central to business decisions and managing risk, said Jennifer Motles, chief sustainability officer at tobacco giant Philip Morris International. “The TNFD recommendations and guidance will support us as we continue to focus on nature-related dependencies, impacts, risks, and opportunities,” Motles said.

The ramp-up in disclosure comes amid heightened awareness of the threat posed to the world by such natural degradation. The top four medium-term risks are all environmental, according to the World Economic Forum’s global risk report published earlier this month. They include extreme weather events, critical changes to the Earth’s systems, a collapse of the ecosystem and natural-resource shortages. “The collective ability to adapt to these impacts may be overwhelmed,” the report warns.

The World Bank estimates that the global economy could lose $2.7 trillion by 2030—which would mean a 10% drop, on average, in the economic output produced across all nations—if certain at-risk ecosystems collapse, such as fisheries or pollination by bees.

Adoption of the TNFD is “a clear signal that investors, lenders, insurers and companies are recognising that their business models and portfolios are highly dependent on both nature and climate,” the taskforce’s co-chair, David Craig, said. Natural risk should be treated both as a strategic risk and an investment opportunity, Craig said.

But reporting the damage done to the natural world isn’t the same as stopping it, said John Tobin-de la Puente, a professor of corporate sustainability at Cornell University. Disclosure is less about encouraging companies to change than it is about giving investors clear information on risk, he said.

Unlike carbon emissions, which can be assessed in terms of metric tons, there isn’t consensus on how to gauge environmental impact—whether, for example, in terms of protected species, general biodiversity, or a bundle of measures, said Tobin, a tropical ecologist and corporate lawyer by training. Some efforts have been made to create units of ecosystem impact, but for now, no universal metric exists, he said.

Alternatives to current business models will also need to be created, just as renewable energy has been developed to replace fossil fuels, Tobin said. “Will we get there at some point soon, before it’s too late for the biosphere?” he asked. “That question is still open.”

A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.

The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.

The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.

The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.

This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.

The debt behind the AI build-out

Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.

Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.

JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.

The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.

That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.

A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.

When interest rates rise, those assumptions become less forgiving.

Inflation changes the calculation

September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.

The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.

CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.

Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.

Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.

The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.

China adds another source of pressure

Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.

Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.

The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.

That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.

A reset rather than the end of the boom

The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.

What has changed is the market’s willingness to overlook the price and financing structure of that growth.

The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.

More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.

For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.

Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.

The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.

Fact box

Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026

Philadelphia Semiconductor Index: Down approximately 11.4 per cent

Micron Technology: Down approximately 14.6 per cent

Samsung Electronics: Down approximately 18 per cent

SK Hynix: Down approximately 24 per cent

US September inflation: 3.7 per cent annually

Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion