AI has emerged as a transformative force, with the potential to revolutionise sectors from healthcare to transport and igniting a wave of innovation not seen in years – perhaps since the early days of the internet. This has driven billions of dollars’ worth of investment into AI infrastructure and helped propel stocks such as Nvidia into the stratosphere. Nvidia has seen its shares soar by a staggering 259% over the past year, fuelled by insatiable demand for its AI chips. However, investors have learnt that what goes up must come down, and the hope and hype of 2023 is giving way to apprehension following concerns about the sustainability of the sky-high valuations of AI-driven stocks. Can this rally endure?

Some experts, among them Apollo chief economist Torsten Sløk, have sounded the alarm, warning of a looming bubble reminiscent of the tech euphoria of the late 1990s, with today’s top S&P 500 companies arguably more overvalued than their 1990s counterparts. However, amid the caution, there’s a chorus of optimism, and so the debate rages on about whether the generative AI stock bubble will or won’t burst. In these cases, history can serve as a useful guide. Capex cycles, rooted in technology, trace back to events such as the UK railway bubble of the 1800s, where rapid infrastructure expansion eventually led to enduring economic growth, despite initial turmoil. The examples of electricity and computing make a similar point. It took decades from the discovery of electricity in the early 1800s for it to significantly influence society. As the technology became more affordable and user-friendly, its adoption became widespread. Similarly with computers, it wasn’t until 1995, more than 25 years after the introduction of the first mass-market computer, that both growth and productivity began to shift notably.

Drawing from this, it seems sensible to infer that the surge in AI infrastructure investment – accelerated by the introduction of consumer-friendly interfaces such as Bard and ChatGPT – will drive future innovation by lowering the barriers and costs of product development. However, despite the promise of generative AI, the reality is that that potential doesn’t immediately translate into solid productivity or revenue gains. While capex cycles that diffuse general-purpose technologies often lead to significant productivity enhancements, these typically come with a lag.

In the case of AI, the question that needs to be answered now that we have the infrastructure and the tools in place is what are we going to use this infrastructure to do? How is it going to change people’s lives? And how are companies going to monetise the AI tools that they make?

While AI represents a seismic shift, the road to widespread transformation is still unfolding, with many industries yet to witness an ‘iPhone moment’ that reshapes productivity and behaviour.

Long-term winners in the AI race may not be the first to monetise the technology, and disruptive shifts may destabilise established players while creating opportunities for newcomers. If generative AI knocks down entry barriers in different industries, as we expect, new players will emerge.

As always, patient investors with a long-term horizon will be looking to identify those companies with distinctive business models and competitive advantages that are poised to benefit from the long-term AI disruption.

By Sasha Planting