Investing in nature to address climate change, support biodiversity, and protect ocean health—and more—is expected to reach record levels this year in response to more regulation and market demand, according to Cambridge Associates, a global investment firm.
Still, the amount of private capital invested to support natural systems will fall far short of what’s needed, according to the annual “State of Finance for Nature” report published in December from the United Nations Environment Programme.
A big reason is that nearly US$7 trillion in public and private finance was directed to companies and economic activities in 2022 that caused direct harm to nature, while only US$200 billion was directed to so-called nature-based solutions, or NbS—investments that protect, conserve, restore, or engage in the sustainable management of land and water ecosystems, as defined by the United National Environment Assembly 5, or UNEA5, the report said.
“Without a big turnaround on nature-negative finance flows, increased finance for NbS will have limited impact,” it said.
But the report also said that the misalignment “represents a massive opportunity to turn around private and public finance flows” to meet targets set by the United Nations Rio Conventions on climate change, desertification, and biodiversity loss.
The conventions aim to limit climate change to 1.5 degree Celsius above pre-industrial levels, protect 30% of the earth’s land and seas by 2030, and to reach “land degradation neutrality” by 2030. Reaching those goals will require more than double the amount of current levels of nature-based investing by 2025, to US$436 billion, and nearly triple today’s levels to US$542 billion by 2030, the report said.
Most of the US$200 billion invested in NbS today is by governments, but private investors contributed US$35 billion—including US$4.6 billion via impact investing funds and US$3.9 billion via philanthropy. The largest source of private finance was in the form of biodiversity offsets and credits. [An offset is designed to compensate for biodiversity loss, while a credit is the asset created to restore it].
Many wealthy individuals and families concerned about climate change and the environment so far have focused their investment dollars on climate solutions and innovations in technology and infrastructure, or in technologies supporting food and water efficiency, says Liqian Ma, head of sustainable investment at Cambridge Associates.
But “increasingly there is growing awareness that nature provides a lot of gifts and solutions if we prudently and responsibly manage nature-based assets,” Ma says.
Investments can be made, for instance, in sustainable forestry and sustainable agriculture—which can help sequester carbon—in addition to wetland mitigation, conservation, and ecosystem services.
“Those areas are not in the mainstream, but they are additional tools for investors,” Ma says.
Finance Earth, a London-based social enterprise, is among the organizations working to make these tools more mainstream by creating a wider array of nature-based solutions in addition to related investment vehicles.
Finance Earth groups nature-based solutions into six themes: agriculture, forestry, freshwater, marine/coastal, peatland, and species protection. Supporting many of these areas are an array of so-called ecosystem services, or benefits that nature provides such as absorbing carbon dioxide, boosting biodiversity, and providing nutrients, says Rich Fitton, director of Finance Earth.
Each of these ecosystem services are behind existing and emerging markets. Carbon-related disclosure requirements (at various stages of approval in the U.S. and elsewhere) have long spurred demand for carbon markets, the most mature of these markets.
Cambridge Associates, for instance, works with dedicated asset managers who have been approved by the California Air Resources Board to buy carbon credits, Ma says.
In its annual investment outlook, the firm said California’s carbon credits should outperform global stocks this year as the board is expected to reduce the supply of available credits to meet the state’s emission reduction targets. The value of these credits is expected to rise as the supply drops.
In September, the G20 Task Force on Nature-Related Financial Disclosures released recommendations (similar to those put forward several years ago by the Task Force for Carbon-related Financial Disclosure) that provide guidance for how companies can look across their supply chains to assess their impact on nature, water, and biodiversity “and then start to understand what the nature-related risks are for their business,” Fitton says.
The recommendations will continue to spur already thriving biodiversity markets, which exist in more than 100 countries including the U.S. In the U.K., a new rule called “Biodiversity Net Gain” went into effect this month requiring developers to produce a 10% net gain in biodiversity for every project they create.
Though developers can plant trees on land they’ve developed for housing, for example, they also will likely need to buy biodiversity credits from an environmental nonprofit or wildlife trust to replace and add to the biodiversity that was lost, Fitton says.
This new compliance market for biodiversity offsets could reach about £300 million (US$382 million) in size, he says.
Finance Earth and Federated Hermes are currently raising funds for a U.K. Nature Impact Fund that is likely to invest in those offsets in addition to other nature-based solutions, including voluntary offset markets for biodiverse woodlands and for peatlands restoration.
The fund was seeded with £30 million from the U.K. Department for Environment, Food and Rural Affairs—money that is designed to absorb first losses, should that be needed. The government investment gives mainstream investors more security to step into a relatively new sector, Fitton says.
“We need the public sector and philanthropy to take a bit more downside risk,” he says. That way Finance Earth can tell mainstream investors “look, I know you haven’t invested in nature directly before, but we are pretty confident we’ve got commercial-level returns we can generate, and we’ve got this public sector [entity] who’s endorsing the fund and taking more risk,” Fitton says.
Since December 2022, when 188 government representatives attending the UN Biodiversity Conference in Montreal agreed to address biodiversity loss, restore ecosystems, and protect indigenous rights, several asset managers began “creating new strategies or refining strategies to be more nature or biodiversity focused,” Ma says.
He cautioned, however, that some asset managers are more authentic about it than others.
“Some have taken it seriously to hire scientists to do this properly and make sure that it’s not just a greenwashing or impact-washing exercise,” Ma says. “We’re starting to see some of those strategies come to market and, in terms of actual decisions and deployments, that’s why we think this year we’ll see a boost.”
Fitton has noticed, too, that institutional investors are hiring experts in natural capital, recognising that it’s a separate asset class that requires expertise.
“When that starts happening across the board then meaningful amounts of money will move,” he says. “There’s lots of projects there, there’s lots of things to invest in and there’ll be more and more projects to invest in as more of these markets become more and more mature.”
From making unpopular decisions to learning when to listen, leaders from five businesses reveal what nobody prepared them for — and how running a company has challenged their expectations.
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.
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
Here’s how they are looking at artificial intelligence, interest rates and economic pressures.
The Swiss watchmaker’s first collaboration with Atlassian Williams F1 Team produces two sporting Laureato models inspired by the team’s 2026 racing car.










