AI investing is shifting beyond Nvidia as memory chip demand surges, with Micron and others emerging as key players in the next phase.
Every major technological revolution begins with a handful of obvious winners. Over time, however, the story broadens as new bottlenecks emerge and a wider ecosystem of companies begins to benefit. Artificial intelligence appears to be entering that phase now.
For much of the past two years, Nvidia has dominated the AI investment narrative. Its graphics processors became the indispensable engines powering the world’s most advanced AI models, propelling the company into the ranks of the world’s most valuable businesses.
The shift to infrastructure: memory becomes critical
Last week, however, another company reminded investors that AI is becoming much bigger than one stock. Micron, the memory-chip maker, stunned markets after reporting another exceptional result, revenue surging from around US$9 billion (NZ$15.9b) a year earlier to nearly US$42b. Its share price jumped around 15% as management pointed to extraordinary demand for AI infrastructure and little sign of supply catching up any time soon. More importantly, the result highlighted that the AI investment cycle is entering a new phase. The first wave was about computing power. The second appears to be about everything that supports it.
Investors have already begun recognising that shift. While Nvidia has spent much of this year consolidating after its extraordinary gains, both Micron and SK Hynix have seen their share prices rise by more than 300% as the market increasingly appreciates the strategic importance of advanced memory.
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Why memory chips are the new bottleneck
Most people think AI is driven primarily by processors. In reality, every AI model also depends on enormous amounts of memory, networking capacity, data-centre infrastructure, electricity and cooling. As AI systems become larger and more sophisticated, each of those components is becoming a critical bottleneck. Markets have always rewarded companies that solve bottlenecks. Railways needed steel. The internet needed fibre-optic networks. Electric vehicles need batteries. Artificial intelligence increasingly needs memory.
Only three companies dominate advanced high-bandwidth memory globally: Micron, SK Hynix and Samsung. As demand has exploded, supply has struggled to keep pace, transforming what was once viewed as a cyclical corner of the semiconductor industry into one of the hottest parts of global markets.
The shortage has now become so acute that some analysts have labelled it “RAM-ageddon”. The world’s largest technology companies are effectively competing with each other for scarce memory chips, with AI data centres consuming an ever-growing share of global supply.
Rising costs ripple through global technology markets
Perhaps the strongest evidence of memory’s growing importance came not from Micron itself, but from Apple and Microsoft. Both recently announced price increases on a range of products after unprecedented rises in memory costs, while manufacturers including Dell, HP, Lenovo and Asus have either lifted prices or reduced memory specifications to offset soaring component costs. When even Apple – widely regarded as having one of the world’s most sophisticated supply chains – is forced to pass on higher component costs, it tells you something important about where pricing power now sits.
In other words, the AI boom is no longer simply lifting technology share prices. It is beginning to influence prices paid by consumers and businesses around the world. What was once viewed as a relatively commoditised part of the semiconductor industry has rapidly become a strategic constraint on the global economy.
Lessons from past technology investment cycles
History suggests this should not surprise investors.
During California’s gold rush, some of the greatest fortunes were made not by the prospectors themselves but by businesses supplying the picks, shovels and durable clothing. Levi Strauss became one of the world’s most recognisable brands without mining an ounce of gold. Technology revolutions tend to work the same way. The internet boom did not simply create Microsoft and Cisco. It produced winners across fibre optics, networking equipment, semiconductors, cloud computing and eventually e-commerce. Artificial intelligence increasingly appears to be following the same path.
In many respects, this is exactly what investors are witnessing today. The extraordinary profitability now being enjoyed by Micron reflects the same shortages forcing Apple and Microsoft to raise prices. Pain for technology manufacturers has become gain for memory producers.
Valuations, risks and what investors should watch next
Yet every time another AI stock surges, comparisons with the dotcom bubble inevitably return. On the surface, the comparison is understandable. Technology companies dominate headlines, a handful of stocks are driving market returns, and artificial intelligence has become one of the world’s biggest investment themes. But beneath the surface, today’s market looks fundamentally different.
During the late 1990s, valuation discipline largely disappeared. Investors famously stopped talking about price-to-earnings ratios and instead embraced “price-to-eyeballs”, valuing internet businesses on website traffic rather than profits. Companies with little revenue, no earnings and often nothing more than a “.com” suffix attracted billion-dollar valuations.
Today’s AI leaders are generating extraordinary profits. Nvidia trades on around 20 times forward earnings despite growing earnings by more than 70% year-on-year. Micron and SK Hynix, both now valued at more than US$1 trillion, trade on fewer than nine times expected earnings over the next 12 months despite being among the biggest beneficiaries of AI infrastructure spending. Those are not valuation multiples normally associated with speculative bubbles. If anything, they suggest investors remain surprisingly disciplined despite extraordinary earnings growth.
There are signs that valuation discipline has returned more broadly across the technology sector. Reports suggest OpenAI is increasingly pushing any blockbuster public listing towards 2027 rather than rushing to market. That is not because demand for artificial intelligence has faded. Quite the opposite. It reflects a market that has become far more discerning about valuation. Following the more muted post-listing performance of SpaceX, investors appear less willing to pay any price for even the world’s highest-profile growth companies.
The money is still there. The blind faith is not.
There is another reason today’s market feels different.
There is an old story that Joseph Kennedy decided to sell his shares shortly before the Wall Street Crash after receiving stock tips from a shoeshine boy. His conclusion was simple: if everyone was speculating, there were few buyers left.
I often think about that story because I experienced something remarkably similar while living in Dublin during the technology boom of the late 1990s. Almost without fail, every week taxi drivers would offer unsolicited recommendations for the latest internet stock that “couldn’t miss”. Investing had become part of everyday conversation, and there was a widespread belief that technology shares could only go higher.
That is not to say speculation does not exist today. It clearly does. But the conversation feels fundamentally different. Most discussions are about how artificial intelligence will reshape businesses, which companies will benefit most and whether earnings can justify valuations, rather than simply chasing the next stock tip.
None of this removes the need for caution. The memory industry remains highly cyclical, competition will intensify and today’s shortages could become tomorrow’s oversupply. Leadership within AI will almost certainly continue to rotate.
But that is precisely the point.
The biggest winners from transformational technologies rarely remain confined to the first obvious company. As industries mature, opportunities migrate deeper into the supply chain as new bottlenecks emerge.
Nvidia may have ignited the AI revolution.
Micron’s latest result suggests the next wave of winners is already emerging.
The lesson for investors is that the biggest opportunities in a technological revolution rarely remain confined to the first obvious company. Sometimes the real fortunes are made by those quietly supplying the picks and shovels.