The Bill for Offshore Wind Power Is Rising
Prices in recent offshore auctions have increased by anywhere from 20% to 70%
3 min
With offshore wind projects bleeding cash, governments will have to pay more to hit their clean-energy targets. Recent auctions show just how much more.
Higher prices for steel, labor and debt financing have raised the cost of developing a wind farm by almost 40% since 2019. It is a big problem for developers like Danish energy company Ørsted, which signed power supply agreements a few years ago at prices that no longer cover today’s costs.
Developers’ struggles are having a knock-on effect on the turbine makers that supply them, including Vestas, GE and Siemens Energy. The latter’s wind unit, Siemens Gamesa, lost €4.3 billion in the company’s latest fiscal year, equivalent to $4.7 billion at current exchange rates—although its issues are mainly with faulty onshore turbines rather than offshore ones.
Germany last week stepped in with a multi-billion-euro state-backed guarantee for Siemens Energy, which told investors at a capital markets day on Tuesday that its wind division won’t make a profit until after 2026. GE says its offshore wind business will lose $1 billion this year, and the same again in 2024.
The industry’s deepest challenges are in the U.S., a market that was meant to be the next growth frontier following the Biden administration’s pledge to install 30 gigawatts of offshore capacity by 2030. Instead, developers are taking multibillion-dollar impairments on U.S. projects, or backing out entirely. According to BloombergNEF, of the 21.6 gigawatts of offshore wind power awarded or signed so far in the U.S., a quarter has been canceled and almost another third is at risk.
Governments are now responding by topping up the prices at which they auction off licenses. Britain was forced to raise its guaranteed price for offshore wind power by 66% after a September auction didn’t attract a single bid. The average price in New York’s latest offshore wind auction in October was a fifth higher than previous rounds, according to BloombergNEF, and the bill could rise further as new contracts include inflation protection that will shield developers from future cost pressures.
Paying higher, more flexible prices for fresh contracts might still end up being a cheaper solution for New York than renegotiating old ones. Developers including BP and Equinor asked for increases of 49% on average over what was agreed in their original power supply contracts. They may pull out after getting a no from the state.
Governments and companies had become used to the cost of renewable energy heading only one way. The global average levelized cost of electricity generated by offshore wind—a measure of the minimum price necessary to cover the lifetime costs of a project—has plunged by 66% since 2009, according to BloombergNEF data.
After years of becoming more competitive as a source of power, offshore wind is beginning to look expensive in some markets compared with fossil-fuel alternatives. Globally, new offshore wind projects still work out cheaper than natural gas ones and are level with coal. But offshore wind looks costly in the U.S., partly because the supply chain is so immature and will need heavy investment for several years.
The new reality makes it harder for governments to meet their net-zero targets while also keeping power costs low for the public. But densely populated areas like New York may not have much choice but to exploit offshore wind. Clean alternatives such as land-based wind and solar farms are tough to roll out where space is at a premium.
The European Union is also aware that if governments don’t do more to support local companies like Siemens Energy, Chinese turbine manufacturers that enjoy generous subsidies from Beijing will be only too happy to step in. This would help the EU stay on track with an ambitious plan to increase its offshore wind capacity sevenfold by 2030, but at the expense of the bloc’s energy independence.
Harnessing the winds out at sea is still a key part of countries’ plans to cut their carbon emissions and boost energy security. But governments can no longer pretend that these political objectives can come cheap.
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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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