A Drop in Interest Rates Could Boost Renewables

If the Federal Reserve cuts interest rates in the coming weeks, a friendlier borrowing environment could make all the difference for some mothballed renewable-energy projects.

The returns generated by such projects once they are up and running are often predictable and modest, but because they require a large upfront expenditure, frequently funded in part by debt, they are sensitive to interest-rate fluctuations.

With recent economic data suggesting the Fed has plenty of room to cut, some investors say now is the time to get moving on renewable plans.

Thomas Byrne, chief executive at solar investor CleanCapital, said a drop in interest rates would affect a “not inconsequential amount” of solar developments under consideration. “We have had projects on hold that simply don’t make economic sense for us anymore because the borrowing cost was too high. So those projects will immediately unlock,” he said.

Byrne estimates some of these projects could begin construction by the end of the year and start generating energy next summer.

Solar and wind energy in particular stand to gain from lower borrowing costs, said Srinivasan Santhakumar, principal research analyst with the research firm Wood Mackenzie. “Higher interest rates have disproportionately affected the economics of wind and solar projects,” he said.

An interest-rate increase of 2 percentage points could result in a 20% jump in the cost of producing energy for utility-scale solar power over the life cycle of a project, according to a Wood Mackenzie analysis released in April. In comparison, the same increase might boost the cost of producing energy from gas by 10% to 12%.

Some developers may wait to see a steeper drop before making moves. “It’s definitely a phenomenon, particularly for the more sophisticated, more longer-standing developers who’ve had a history of surfing the ups and downs of the interest-rate spectrum and are also aware of the consequences for their own balance sheet of a long-term interest rate rise,” said Katherine Mogg, managing director at the New York Green Bank, a state-sponsored investment fund that focuses on filling gaps in energy transition financing. Mogg said she expects to see a modest uptick in requests for proposals in the coming months.

The Federal Reserve has signalled a rate cut at its next meeting in September, and most futures investors expect a quarter-percentage-point reduction, according to CME FedWatch. More than three quarters of investors expect the Fed to lower its benchmark rate, now in a range between 5.25% and 5.5%, by at least a full percentage point by year-end.

While a cut in interest rates is a positive for renewables financing, a durable boost for green projects may require a Goldilocks economic scenario in which a cut to borrowing costs don’t coincide with rising fears of a global recession, which could in turn drive investors away from the U.S., said Ron Erlichman, partner at the law firm Linklaters.

“There are a lot of different factors, like the old cliché of ‘headwinds,’ that affect transactions,” he said, adding that large-scale projects such as offshore wind, hydrogen and carbon capture frequently rely on foreign investment.

Fears of unchecked inflation and rampant increases in the cost of materials have cooled down somewhat in the past year, he said, but the looming U.S. election brings a fresh element of uncertainty . While many see a low probability of a full rollback of the Inflation Reduction Act, the legislation that provides game-changing tax breaks for renewables, an executive branch hostile to green energy could slow project permitting or otherwise “nibble at the fringes” of the landmark legislation, as Byrne put it.

“Having done this awhile and seen the cycles in the market, I still remain incredibly optimistic about renewables and energy transition in the United States,” Erlichman said.

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