Only for a second final week, Larry Ellison, co-founder of US cloud computing firm Oracle, turned the world’s richest particular person.
The octogenarian tech titan briefly overtook Elon Musk after Oracle’s share worth rocketed 43% in a day, including about US$100 billion (A$150 billion) to his wealth.
The explanation? Oracle inked a deal to supply synthetic intelligence (AI) large OpenAI with US$300 billion (A$450 billion) in computing energy over 5 years.
US president Donald Trump with Softbank’s Masayoshi Son, Oracle’s Larry Ellison and OpenAI’s Sam Altman.
Whereas Ellison’s second within the highlight was fleeting, it additionally illuminated one thing way more vital: AI has created extraordinary ranges of focus in world monetary markets.
This raises an uncomfortable query not just for seasoned traders – but additionally for on a regular basis Australians who maintain shares in AI firms through their superannuation. Simply how uncovered are even our supposedly “safe”, “diversified” investments to the AI growth?
The person who constructed the web’s reminiscence
As billionaires go, Ellison isn’t as a lot of a family title as Tesla and SpaceX’s Musk or Amazon’s Jeff Bezos. However he’s been constructing wealth from enterprise know-how for almost 5 many years.
Ellison co-founded Oracle in 1977, reworking it into one of many world’s largest database software program firms. For many years, Oracle supplied the unglamorous however important plumbing that stored many company programs operating.
The AI revolution modified all the pieces. Oracle’s cloud computing infrastructure, which helps firms retailer and course of huge quantities of knowledge, turned essential infrastructure for the AI growth.
Each time an organization desires to coach massive language fashions or run machine studying algorithms, they want large quantities of computing energy and knowledge storage. That’s exactly the place Oracle excels.
When Oracle reported stronger-than-expected quarterly earnings this week, pushed largely by hovering AI demand, its share worth spiked.
That response wasn’t nearly Oracle’s enterprise fundamentals. It was about your complete AI ecosystem that has been reshaping world markets since ChatGPT’s public debut in late 2022.
The nice AI focus
Oracle’s story is a part of a a lot bigger phenomenon reshaping world markets. The so-called “Magnificent Seven” tech shares – Apple, Microsoft, Alphabet, Amazon, Meta, Tesla and Nvidia – now management an unprecedented share of main inventory indices.
12 months-to-date in 2025, these seven firms have come to characterize roughly 39% of the US S&P500’s complete worth. For the tech-heavy NASDAQ100, the determine is a whopping 74%.
This implies should you put money into an exchange-traded fund that tracks the S&P500 index, usually thought-about the gold normal of diversified investing, you’re making an more and more concentrated guess on AI, whether or not you realise it or not.
Are we in an AI ‘bubble’?
This degree of focus has not been seen because the late Nineties. Again then, traders have been swept up in “dot-com mania”, driving know-how inventory costs to unsustainable ranges.
When actuality lastly hit in March 2000, the tech-heavy Nasdaq crashed 77% over two years, wiping out trillions in wealth.
Immediately’s AI focus raises some comparable purple flags. Nvidia, which controls an estimated 90% of the AI chip market, at the moment trades at greater than 30 instances anticipated earnings. That is costly for any inventory, not to mention one carrying the hopes of a complete technological revolution.
But, not like the dot-com period, at the moment’s AI leaders are worthwhile firms with actual income streams. Microsoft, Apple and Google aren’t cash-burning startups. They’re established giants, utilizing AI to reinforce current companies whereas producing substantial earnings.
This makes the present state of affairs extra sophisticated than a easy “bubble” comparability. The tutorial literature on market bubbles suggests real technological innovation usually coincides with speculative extra.
The query isn’t whether or not AI is transformative; it clearly is. Quite, the query is whether or not present valuations replicate real looking expectations about future profitability.
Hidden publicity for a lot of Australians
For Australians, the AI focus drawback hits remarkably near residence by way of our superannuation system.
Many balanced tremendous fund choices embody substantial allocations to worldwide shares, usually 20–30% of their portfolios.
When your tremendous fund buys worldwide shares, it’s usually getting heavy publicity to those self same AI giants dominating US markets.
The focus threat extends past direct investments in tech firms. Australian mining firms, akin to BHP and Fortescue, have turn out to be oblique AI gamers as a result of their copper, lithium and uncommon earth minerals are important for AI infrastructure.
Even diversifying away from know-how doesn’t totally escape AI-related dangers. Analysis on portfolio focus exhibits when main indices turn out to be dominated by a couple of massive shares, the advantages of diversification diminish considerably.
If AI shares expertise a big correction or crash, it might disproportionately impression Australians’ retirement nest eggs.
A actuality verify
This example represents what’s known as “systemic concentration risk”. It is a particular type of systemic threat the place supposedly diversified investments turn out to be correlated by way of widespread underlying elements or exposures.
It’s paying homage to the 2008 monetary disaster, when seemingly separate housing markets throughout completely different areas all collapsed concurrently. That was as a result of they have been all uncovered to subprime mortgages with excessive threat of default.
This doesn’t imply anybody ought to panic. However regulators, tremendous fund trustees and particular person traders ought to all pay attention to these dangers. Diversification solely works if returns come from a broad vary of firms and industries.
Angel Zhong, Professor of Finance, RMIT College and Jason Tian, Senior Lecturer, Swinburne College of Expertise
This text is republished from The Dialog underneath a Inventive Commons license. Learn the unique article.
