Investments in Solar Power Eclipse Oil for First Time
Government spending, including Biden’s Inflation Reduction Act, has helped drive a gap between clean-energy spending and fossil-fuel investments
3 min
Investments in solar power are on course to overtake spending on oil production for the first time, the foremost example of a widening gap between renewable-energy funding and stagnating fossil-fuel industries, according to the head of the International Energy Agency.
More than $1 billion a day is expected to be invested in solar power this year, which is higher than total spending expected for new upstream oil projects, the IEA said in its annual World Energy Investment report.
Spending on so-called clean-energy projects—which includes renewable energy, electric vehicles, low-carbon hydrogen and battery storage, among other things—is rising at a “striking” rate and vastly outpacing spending on traditional fossil fuels, Fatih Birol, the IEA’s executive director said in an interview. The figures should raise hopes that worldwide efforts to keep global warming within manageable levels are heading in the right direction, he said.
Birol pointed to a “powerful alignment of major factors,” driving clean-energy spending higher, while spending on oil and other fossil fuels remains subdued. This includes mushrooming government spending aimed at driving adherence to global climate targets such as President Biden’s Inflation Reduction Act.
“A new clean global energy economy is emerging,” Birol told The Wall Street Journal. “There has been a substantial increase in a short period of time—I would consider this to be a dramatic shift.”
A total of $2.8 trillion will be invested in global energy supplies this year, of which $1.7 trillion, or more than 60% will go toward clean-energy projects. The figure marks a sharp increase from previous years and highlights the growing divergence between clean-energy spending and traditional fossil-fuel industries such as oil, gas and coal. For every $1 spent on fossil-fuel energy this year, $1.70 will be invested into clean-energy technologies compared with five years ago when the spending between the two was broadly equal, the IEA said.
While investments in clean energy have been strong, they haven’t been evenly split. Ninety percent of the growth in clean-energy spending occurs in the developed world and China, the IEA said. Developing nations have been slower to embrace renewable-energy sources, put off by the high upfront price tag of emerging technologies and a shortage of affordable financing. They are often financially unable to dole out large sums on subsidies and state backing, as the U.S., European Union and China have done.
The Covid-19 pandemic appears to have marked a turning point for global energy spending, the IEA’s data shows. The powerful economic rebound that followed the end of lockdown measures across most of the globe helped prompt the divergence between spending on clean energy and fossil fuels.
The energy crisis that followed Russia’s invasion of Ukraine last year has further driven the trend. Soaring oil and gas prices after the war began made emerging green-energy technologies comparatively more affordable. While clean-energy technologies have recently been hit by some inflation, their costs remain sharply below their historic levels. The war also heightened attention on energy security, with many Western nations, particularly in Europe, seeking to remove Russian fossil fuels from their economies altogether, often replacing them with renewables.
While clean-energy spending has boomed, spending on fossil fuels has been tepid. Despite earning record profits from soaring oil and gas prices, energy companies have shown a reluctance to invest in new fossil-fuel projects when demand for them appears to be approaching its zenith.
Energy forecasters are split on when demand for fossil fuels will peak, but most have set out a timeline within the first half of the century. The IEA has said peak fossil-fuel demand could come as soon as this decade. The Organization of the Petroleum Exporting Countries, a cartel of the world’s largest oil-producing nations, has said demand for crude oil could peak in developed nations in the mid-2020s, but that demand in the developing world will continue to grow until at least 2045.
Investments in clean energy and fossil fuels were largely neck-and-neck in the years leading up to the pandemic, but have diverged sharply since. While spending on fossil fuels has edged higher over the last three years, it remains lower than pre pandemic levels, the IEA said.
Only large state-owned national oil companies in the Middle East are expected to spend more on oil production this year than in 2022. Almost half of the extra spending will be absorbed by cost inflation, the IEA said. Last year marked the first one where oil-and-gas companies spent more on debt repayments, dividends and share buybacks than they did on capital expenditure.
The lack of spending on fossil fuels raises a question mark around rising prices. Oil markets are already tight and are expected to tighten further as demand grows following the pandemic, with seemingly few sources of new supply to compensate. Higher oil prices could further encourage the shift toward clean-energy sources.
“If there is not enough investment globally to reduce the oil demand growth and there is no investment at the same time [in] upstream oil we may see further volatility in global oil prices,” Birol 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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