Investing in the AI trade – is it too late or still early?

Artificial intelligence (AI) has dominated headlines, boardroom discussions, and investor presentations for the past three years.

Since the release of ChatGPT in late 2022, the technology has been hailed as transformative – promising to revolutionise industries, boost productivity, and unlock trillions in economic value.

But as we approach the latter half of the decade, a critical question still looms – are we still early in the AI trade, or has the hype already peaked?

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AI investment is not slowing

Some forecasts suggest AI could unlock $40trn in operational efficiencies globally, triggering a wave of investment in the coming years. This suggests that the current phase, dominated by data centre buildouts and language model development, is laying the groundwork for a decade-long transformation.

The great thing about public markets is that we don’t have to guess what companies are spending on the AI buildout. Recent results and guidance from some of the biggest AI investors in the world paint an obvious picture.

The world’s largest companies have sharply increased investment, and while not all of it goes to AI, the majority of the additional spend is directed there.

Show me the return

Sceptics often point out the lack of obvious AI revenue from all this investment, and we certainly see merit to that point of view.

NVIDIA CEO Jensen Huang thinks AI infrastructure spending could hit $3–$4trn by 2030.

But where are the game-changing products and services?

In our view, it's only a matter of time. But we’re also conscious that new technologies often take longer to embed than people think.

A recent MIT study backs up this point.

It found that 95% of generative AI pilots at companies are failing. The problem isn’t the AI itself, but more broadly, a lack of expertise and knowledge of how to integrate this new technology into businesses.

Cost improvement, not revenue growth, is the place to look

We tend to think markets get this wrong. Rather than looking for new revenue to suddenly appear, which will take time, we’ve been looking at how companies are using AI to become more efficient.

Flip that MIT study on its head, and there’s a small cohort of companies making AI work today – those are businesses that now have a distinct advantage over the competition.

From our experience, the biggest companies tend to shout the most about AI wins. That makes sense logically – the tech titans already have vast pools of software and AI talent on the books, so we’d expect them to be early adopters.

The numbers seem to back up our thesis. Operating efficiency (which looks at operating costs compared to revenue) has been improving (lower is better), and revenue per employee has also taken a meaningful step higher.

This suggests the tech giants are doing more with less, and the timing coincides with AI adoption.

The great bubble debate

We often hear the current AI-fuelled market compared to bubbles of bygone years, the dotcom crash perhaps one of the most common.

Yes, the market is concentrated, and yes, valuations are higher than we’ve seen in recent years. But if we look at the tech-heavy Nasdaq 100 index, the earnings multiple isn’t in crazy territory.

We also think the current group of market leaders are significantly stronger operationally and financially than the bubble stocks of the dotcom era.

The big get bigger – for now

So, who wins from all this?

We think the big names have an advantage early on, but only if they’re taking the right steps now.

There are clear early winners from Meta to NVIDIA, and then obvious laggards like Apple, who have yet to really tap into the benefits of AI but still have time to get on track.

More broadly, our view is that we’re in the early stages of the AI transition. The road ahead will no doubt have bumps, but longer-term investors should position themselves to benefit from one of the biggest mega trends we’ve seen for some time – as part of a diversified portfolio.

Disruption will play a major part in the coming years as the corporate landscape evolves. Those who adapt could thrive – the rest risk being left in the dust.

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The author holds shares in NVIDIA.

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