Why ESG Investing Might Never Recover

The ESG brand probably has its best days behind it.

Following a three-year craze for investment products focused on environmental, social and corporate-governance concerns, the percentage of newly created funds in the U.S. and Europe with ESG in their name has fallen from a peak of 8.3% to just 3.3%, according to an analysis of quarterly data by Morningstar Direct.

Likewise, online searches for “ESG investing” have plummeted back to mid-2019 levels, according to Google Trends. Mentions of the term in company analyst calls have dropped 59% from their quarterly peak in 2022, FactSet data suggest.

One explanation is the collapse of the clean-energy stocks most readily associated with the ESG movement. Flagging growth in electric-vehicle sales has hit sector behemoth Tesla . The S&P Global Clean Energy index, which lists solar-panel maker First Solar and Danish wind-turbine giant Vestas among its top constituents, has lost 31% since the start of 2023 as renewable-energy projects have been shelved. That compares with returns of 27% for global stocks.

The rise of ESG investing between 2019 and 2022 coincided with a surge in clean-tech valuations, and now the reverse is happening. Investors have pulled $2.2 billion from funds dedicated to decarbonisation since the start of the year, according to EPFR, and the outflows are getting larger every week.

There is a risk that ESG was an investment fad rather than a financial revolution extending across all industries.

The term was the product of an uneasy three-way alliance. On one side were ethically driven investors, who are particularly widespread in Scandinavia and include pension funds, universities and religious organisations united in wanting to shun contentious firms. On another were institutions such as the United Nations that aimed to channel money to industries that benefit society. Finally, there were investors who wanted to profit from the green revolution.

Asset managers jumped at the chance to cater to all three simultaneously. ESG allowed them to differentiate their products, revitalise the case for active management and, at a time of declining fees, charge more for stock screens that often lead to only small changes in allocations . Among U.S. equity funds, ESG strategies have an asset-weighted average fee of 0.52%, compared with 0.33% overall, Morningstar Direct data shows.

But the confusion of motivations made for contradictions and a lot of doublespeak. Neither ethical objectives nor bets on decarbonisation square logically with fund managers’ claims that ESG is a broad path to higher, safer returns.

Yes, an ESG focus can help active managers account for risks such as a regulatory backlash or governance blow up, which in some cases might be highlighted by new company disclosures. This month the European Union cleared the way toward requiring firms to better report and address sustainability impacts.

However, the assumption that integrating ESG criteria into their screening will lead to better stock picking seems flawed . The very popularity of ESG makes it unlikely that the market is under appreciating the risks. The rush of money into firms like Vestas, whose stock hit a price-to-earnings ratio of 534 in 2022, illustrates the risk that shares with high sustainability scores can get too expensive, leading to lower returns.

Ethical investors might be fine with this, but that just shifts the focus to what counts as ethical. Tellingly, interest in ESG has dropped more in the U.S., where the politicisation of EVs and culture wars surrounding Bud Light beer show how easily corporations can become ideological battlegrounds.

ESG ratings aren’t much help in navigating these issues. Different providers give wildly different scores to the same companies, even within the specific “E,” “S” and “G” factors, according to a February paper by the Leibniz Institute SAFE. Researchers also found that environmental concerns tend to explain most of the overall score.

This is another hint that the ultimate driver of the pandemic-era ESG craze might have been a hunger for thematic investment. It has since found better sources of sustenance, as demonstrated by the breakneck growth of firms such as Global X, which is delivering increasingly granular offerings such as tracker funds for electric batteries, cloud computing and ageing populations.

Buyers of these products can be fickle and jump to the next theme—often too quickly for their own good, a Morningstar analysis showed last November. It is possible that the overly generic ESG brand will never recover its appeal, with the different parts of it eventually rebranded to suit their specific client bases. BlackRock , the world’s largest asset manager, has already dropped it and is now emphasising transition themes over ethical stewardship of companies.

Sustainable investing isn’t going anywhere. But a broad tent covering too many interests serves none of them well.

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