Investing in AI – is it the new modern-day gold rush?

The Californian gold rush that started in 1848 ultimately led to an estimated 300,000 fortune-seekers arriving in the state hoping to strike it rich. However, most did not and from this an old market motto was born.

While a lot has changed since the mid-1800s, we’re now witnessing a new gold rush – artificial intelligence (AI).

But who are the pick and shovel makers in today’s gold rush?

This article isn’t personal advice. All investments can rise and fall in value, so you could get back less than you invest. If you’re not sure if an investment’s right for you, ask for financial advice.

Nvidia – AI’s golden discovery?

If we continue this analogy, the most prolific shovel maker to date must surely be Nvidia.

Once known for providing the Graphics Processor Units (GPUs) that powered games consoles, Nvidia is now far and away the dominant provider of the core kit necessary for running AI applications.

This is because GPUs break down the challenge of rendering graphics by splitting the computational challenge into many thousands of smaller, simultaneous problems. Luckily for Nvidia, that’s the same approach used by generative AI models, making them the provider of choice for AI computing power.

This year alone, Nvidia’s market value has been pushed up by over a trillion dollars to stand at almost $2.4tn. That’s almost 40 times their last reported annual revenue.

Clearly the market is expecting Nvidia to keep growing. Consensus forecasts suggest revenues could rise by around 80% in the current year.

To put Nvidia’s market worth into some perspective, its valuation is not too far shy of the combined $2.6tn value of the entire FTSE 100 index.

Should we be backing the AI shovel makers?

We know in-demand industries can suffer from cost squeezes as they struggle to grow fast enough to meet demand, and this could be a concern for investors.

Demand is also important. If AI allows industries to reduce costs, more output will be consumed only if the demand is there.

For example, if AI halved the cost of toothbrush manufacturing, would we buy more of them? Probably not. But if AI-driven automation within kitchens allowed the cost of great restaurant meals to tumble, we probably would all eat out more often.

Even where there’s demand, there could still be challenges.

The sheer volume of silicon circuitry required for major AI deployments mean that leading chip manufacturers like Taiwan Semiconductor Manufacturing Co. Ltd ought to see strong demand for their services. But whether they can capture enough of the chips’ value for themselves is another matter.

Who will be deploying AI?

So, where should we go looking for AI beneficiaries?

What we’re not seeing so far is companies profitably deploying AI on an industrial scale. The companies that have the people who actually know how to do this are going to be well placed to benefit.

We’re talking about the tech companies, from Microsoft to Accenture, ServiceNow to AutoDesk and IBM.

However, this is where the gold rush analogy becomes blurred, because these companies are both shovel makers and beneficiaries. They have deep expertise in areas like automation, systems integration and connectivity. After all, the AI revolution is about deploying more technology into businesses.

Vast amounts of the computing involved in any AI deployment are likely to take place in the cloud, so the big cloud operators, Amazon, Microsoft and Google are all likely to win business in their already fast-growing operations.

Industrial automation is only going to increase.

Japan is a world-leader in robot technologies. As awareness of AI, and its ability to drive a wave of technological and industrial investment, has risen, the Japanese stock market has awoken from a thirty-year torpor.

It’s now breaching highs that were set way back in the late 1980s. There should be opportunities for the major robotics players, like Fanuc and SMC, to bring further automation into factories worldwide.

The pharmaceutical industry should be able to speed up the identification of drug candidates by harnessing AI. But the process of taking drugs through clinical trials will hopefully remain reassuringly slow. Investors might have to wait many years to see which players have been smartest in how they use the new technology.

What does this mean for investors?

The challenge for investors is to find which companies will be most adept at deploying AI and where the opportunities to gain competitive advantage from it are most compelling.

The more competitive an industry already is, the less likely it is to offer major opportunities for AI to upset the apple cart.

As always, I would caution that investors should be thinking at least as much about the risks as the opportunities. No-one can know for certain how AI will play out. But one outcome does strike me as rather likely – complacent companies will be the losers.

AI should be an enabler and an accelerator of innovation. Any business resting on its laurels could well be at risk if their competitive moat is not extremely wide.

The other risk to be aware of is the propensity for large-scale IT projects to go awry. So even for the innovators, AI is not a risk-free route to wealth creation.

The adoption of AI is underway, but its outcomes are uncertain, raising the risks of volatile outcomes across the market as time identifies the winners and losers.

Perhaps above all, this is an apt reminder to be well diversified in your portfolio. That’s because in all this uncertainty, the chances of keeping a clean sheet could be lower than you might wish.