Global Charities Say Using Companies’ Carbon Offsets to Lower Emissions Undermines Climate Targets

More than 80 global charities and climate industry bodies are voicing their opposition to the use of carbon offsets by companies and countries to lower their carbon emissions, saying that implementing those projects only delays climate action.

Charities including Oxfam, Greenpeace and Amnesty International as well as industry bodies and pressure groups like the European Federation for Transport and Environment and NewClimate Institute signed a letter on Tuesday urging companies to stick to scientifically backed methods to lower carbon emissions and in particular for the Science Based Targets Initiative and the Greenhouse Gas Protocol to continue to exclude carbon offsets from their methodologies on how companies can lower emissions.

“Climate targets must focus primarily on reduction of greenhouse gas emissions within companies’ and countries’ own boundaries, including the phasing out of fossil fuel production, transport, sale and use,” the letter said.

“An urgent scale-up of financial support from both public and private actors is needed for this. But allowing companies and countries to meet climate commitments with carbon credits is likely to slow down global emission reductions while failing to provide anything like the scale of funds needed in the Global South, and reducing pressure to develop large-scale mechanisms such as ‘polluter pays’ fees on emission-intensive sectors,” it added.

Scrutiny of carbon offsets has grown in recent months after the SBTi, a nonprofit organisation that helps companies set targets for lowering emissions, said in April it was considering allowing carbon offsets to be part of the tool kit companies could use to reduce their impacts on the environment. That decision had been in opposition to its longstanding policy of excluding offsets, resulting in backlash from within the organisation itself as well as partner companies like Hennes & Mauritz , better known as H&M.

However, companies in industries from technology to mining argue that offsets are key to reducing private-sector emissions and moving to net zero. Microsoft for example has spent hundreds of millions on carbon offset projects, arguing that without doing so the company wouldn’t be able to move to net zero, especially over its indirect emissions.

“It is about creating a market for high-quality high-integrity durable carbon-removal assets,” said Melanie Nakagawa, Microsoft’s chief sustainability officer in a recent interview . “Think about sequestering carbon into the soils using enhanced rock weathering or rocks that are absorbing carbon that is being turned into concrete. Or Mombak, which is a large forestry project in Brazil. These are the ways that we think about applying it.”

In May, the U.S. government also gave its backing for the voluntary carbon market , saying that “high-integrity” voluntary carbon markets can play a role in reaching net-zero emissions globally.

The letter added that offsetting “at best, doesn’t reduce the concentration of GHGs in the atmosphere, it simply moves emission reductions from one place to another.” The charities also argued that allowing offsets to grow means that high-emitting activities are able to carry on.

To add to this, the charities and industry bodies said that there are only so many high-quality projects that can be used to reduce emissions, meaning that demand is likely to outstrip supply. They also questioned offsets’ effectiveness, saying that their use could just lead to deforestation in other areas or lead to social and environmental harm.

“The science clearly shows that offsets fail to deliver additional emissions reductions and are an unreliable tool for fighting the climate crisis,” the groups added.

A spokesperson for SBTi said that the organisation is still in the research phase of its policy revision. “The Corporate Net-Zero Standard hasn’t been changed, and it cannot and will not change until the Standard Operating Procedure for the revision of the Corporate Net-Zero Standard has been completed,” the spokesperson said.

Microsoft didn’t respond to a request for comment.

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