Companies Urged to Take Stock of Their Impact on Nature and Related Risks
A U.N.-funded task force aims to help businesses report and act on a variety of issues, including deforestation and overfarming
3 min
Companies should consider the natural world as core to their business and report their effect on it in much more detail, according to a U.N.-funded group that promotes sustainable business practices. But assessing environmental impact remains tricky.
The latest draft framework published by the Taskforce on Nature-Related Financial Disclosures aims to help big businesses and financial institutions report and act on nature-related risks, covering issues including deforestation, pollution, water stress and overfarming. It follows previous drafts, with a final version slated to be published in September.
Depletion of resources and damage to rivers and forests should be seen as integral to firms’ operations, and not merely a matter of corporate responsibility, said Tony Goldner, the TNFD’s executive director. “We used to think of nature as an endless supplier of resources into our business practices,” he said. “We’re trying to shift the conversation around the nature of the relationship between nature and business.”
The final framework should give priority to the end result in natural areas, said Kat Bruce, founder and director of environmental-DNA startup NatureMetrics.
“Creating a baseline on the state of nature in…priority areas and then ongoing monitoring to track progress over time is key,” she said, noting that new technology allowed for collection of much more solid biodiversity data.
“We also need to focus on how effective company actions are to mitigate risks,” Ms. Bruce said. The current guidance is a “solid step,” she said. “But we must not stop there.”
The TNFD is a market-led initiative but funded by the United Nations. It brings together 40 corporate executives, including Deputy Environment Director Alexandre Capelli of French luxury-goods group LVMH Moët Hennessy Louis Vuitton SE; GSK PLC head of corporate responsibility Sarah Dyson; Renata Pollini, head of nature at Swiss cement maker Holcim Ltd.; and Koushik Chatterjee, chief financial officer at India’s Tata Steel Ltd.
Some $44 trillion of global economic value is moderately or highly dependent on nature, according to the World Economic Forum. The collapse of natural systems could wipe $2.7 trillion a year from the global economy by 2030, according to the World Bank.
Companies and shareholders should pay more attention to the material risk of natural degradation, Mr. Goldner said. “Dependency is the pathway to risk,” he said. “If you’re investing in a fast-growing agricultural company in an area where there is water stress, that should trigger questions,” he said.
“What does that tell the investor about the ability to keep growing at that same rate?”
The draft framework covers three areas that should be assessed by large companies and financial institutions: the use of land, freshwater and oceans; pollution and pollution removal; and resource use and replenishment. The framework highlights the potential use of bidirectional metrics, that is to say, positive effects as well as negative, Mr. Goldner said.
A fourth indicator, on climate change, is covered by a separate framework set out by the Taskforce on Climate-Related Financial Disclosures, or TCFD.
Companies’ effect on climate change is relatively simple to measure. Emissions can be calculated in metric tons, and companies use shared rules that enable comparisons between one business and another, even if reporting remains patchy and partly based on estimates.
But reaching “nature positive”—as the TNFD aims to achieve—is a more nebulous concept, Mr. Goldner acknowledged. “There’s some work to do reaching a consensus on what nature positive looks like,” he said. It would likely encompass a basket of metrics, rather than a single indicator, he added.
The TNFD’s draft comes after nations agreed on a new international framework that will oblige large corporations to show they are reducing their impact on the world’s natural life.
Public subsidies seen as harmful for biodiversity will be cut by $500 billion a year under the Global Biodiversity Framework, or GBF, reached at the United Nations’ COP15 conference on biodiversity in Montreal in December.
Under the GBF, governments between now and 2030 will introduce laws and policy measures requiring large companies to disclose and reduce the damage done to ecosystems from their operations, supply chains and portfolios. They will also be required to provide information to the public needed for more sustainable consumption.
A previous draft requirement for businesses to reduce their negative impact on the environment by at least half wasn’t included in the final agreement, which doesn’t specify the extent of the required actions. Nearly 200 countries signed on to the final agreement. The U.S. wasn’t an official participant.
The TNFD’s framework aims to help businesses align their reporting and actions to global policy goals, such as the GBF, the task force said. The draft framework includes sector-specific guidance for areas including agriculture, mining, energy and financial services.
Guidance for other industries, including textiles, will be released on a rolling basis over the coming months, the TNFD said.
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Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
4 minA 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
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