The AI hype cycle, News Flash, Dynasty Asset Management

The “hype cycle” is a term popularised by Gartner – a research firm listed on the S&P 500 – and one that is common knowledge in Silicon Valley.

Since the launch of ChatGPT in late 2022, excitement about the potential of artificial intelligence (AI) has helped to power the S&P 500 and Nasdaq indices to new highs. The AI-flavoured Magnificent Seven today account for around 30% of the S&P 500’s total market capitalisation.

The Seven produce the silicon chips needed to build the computers that run AI software (Nvidia), write AI software (Alphabet, Microsoft, Meta), offer cloud computing services (Alphabet, Amazon, Microsoft) and use AI to provide a range of services and applications for businesses and consumers (most of the Seven excluding Nvidia).

The rapid growth that these stocks have experienced over the past two years has led some observers to question whether the hype can be justified. Fears that AI-fuelled stocks are in a bubble no doubt contributed to the massive drops the Seven experienced in the Flash Crash earlier this month – though they have mostly recovered.

While AI still has momentum, we are starting to see a growing chorus of voices asking whether it will meet the market’s inflated expectations. This indicates that the hype around AI is fragile and that all it might take to burst the bubble is some bad macroeconomic news or lower-than-expected earnings from one of the AI bellwether stocks.

The Economist this week cites data from the Census Bureau indicating only 4.8% of American companies use AI to produce goods and services, down from a high of 5.4% early this year. Goldman Sachs, meanwhile, points to an analysis from MIT, which sees only limited US economic upside from AI.

Some of the challenges that sceptics are articulating about generative AI include:

Worries about whether the billions of dollars being pumped into AI will generate commensurate financial returns,
Concerns about the operating costs of services such as OpenAI, which require colossal amounts of fixed and working capital to operate,
Fears about sustainability, rooted in the sheer amount of electricity it takes to run AI queries,
Market burnout following years of exaggerated claims from the tech industry, and
The reality that automating human tasks at scale is harder than many companies realise at first.

As The Economist notes, some technologies go through the classic hype cycle described by Gartner. Following an innovation trigger, they enter a ‘Peak of Inflated Expectations’ when people and companies overestimate how quickly the technology will be adopted. A ‘Trough of Disillusionment’ follows when experiments and implementations fail to deliver, following which the hype cycle enters the ‘Slope of Enlightenment’ and ‘Plateau of Productivity’.

The Internet is a classic example of this hype cycle. However, The Economist notes that some technologies moved into the mainstream in a more linear fashion – like cloud computing. Others, such as 3D printing, virtual reality and autonomous vehicles, have yet to climb out of the ‘Trough of Disillusionment’. It remains to be seen how AI’s hype cycle will play out.

But for now, AI is booming. The likes of Uber and Alphabet’s Waymo are accelerating investments in autonomous cars, which have a heavy AI component. Bloomberg notes that Europe’s biggest industrial companies – ABB, Siemens, Legrand and Schneider Electric – have seen a surge in orders for data centre infrastructure to support the demand for AI.

It is clear, however, that AI stocks are under growing scrutiny. The major players in generative AI may face a crunch when they will need to show that their technology can deliver the exponential improvements in productivity the market is expecting. Those that disappoint may see dramatic drops in value.

We believe that the relative volatility we experienced in AI stocks in August will prevail for the foreseeable future, although we are also convinced that the technology has the potential to dramatically change the world in the months and years to come. Our investment approach aims to capture the gains in leading AI companies such as Nvidia, which have shown exponential increases in market capitalisation, while protecting investors from downside risk. We achieve this through a blend of broad index exposure and concentrated quality-style portfolio building blocks respectively, the latter being more immune to the vagaries of the AI hype cycle.

“We expect AI to transition from a ‘tell me’ to a ‘show me’ story, with any disconnect between investments and revenue generation to come under increased scrutiny. Overweight capex growers that fail to monetise quickly enough could be vulnerable to de-risking.”

– Bank of America report

Global News

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Local News

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As at the time of writing, the rand was flat and the ALSI was 1.5% up for the week.