Investors looking to capitalise on the tech market rally by getting exposure to the companies they think will be the winners from the AI revolution need to remain cautious, realistic and selective.
The hype around the disruptive capabilities of AI – and, in particular, generative AI – has exploded following the launch of ChatGPT. Analysis from US fund house AllianceBernstein (AB), for example, shows that during first-quarter earnings season, about 20% of US and global companies talked about AI on their earnings calls.
The potential of generative AI to transform businesses ranges from virtual assistants for customer support and predictive analytics, to fraud detection and futuristic autonomous vehicles and drones.
Yet delivering business benefits from AI will take time, according to Jonathan Berkow, director of data science, equities at AB. “Investors should proceed with caution.”
Keeping a clear head
While technology companies are inevitably the biggest advocates of AI, it is also high on the agenda in the consumer discretionary, financials, healthcare and industrials sectors, too. Investors have also seen shares of AI enablers surge.
However, the key thing that Berkow believes companies must show investors, is how AI fits into a business model. “They’ll need to prove that the technology works reliably, is embraced by customers, improves productivity and supports earnings.”
For instance, if an AI technology becomes commoditised, its competitive advantages could get eroded, he added. “And [investors should] keep in mind how many of the early dot-com darlings that promised to change the world disappeared without a trace.”
Hyun Ho Sohn, portfolio manager at Fidelity International, reinforces the need for investors to remain cautious or, perhaps, realistic.
“Every technology company seems to be pitching an AI angle. While some stand to make tangible near term gains from AI, most firms seem to be trying to promote AI-related products, with limited and likely near-term customer traction.”
In Berkow’s view, data science can help investors begin to sort the strategic thinkers from publicity seekers. “By asking the right questions as part of a fundamental research process, equity investors can then identify the truly innovative companies that will successfully plug AI applications into a broader business strategy to ultimately enhance investment returns,” he added.
Driving demand for enablers
A key growth area benefiting from AI adoption is the supply and demand of semiconductors.
Given that semiconductors are the backbone of technological innovation, Anjali Bastianpillai, senior client portfolio manager, thematic equities, Pictet Asset Management, believes the sector is expected to become a trillion-dollar industry by 2030. “We are positive about the impact of AI on the semiconductor market and how it will affect government and enterprise supply chain resilience.”
This is spurred by the resource intensive nature of AI, which requires vast amounts of data and processing power to create new content.
“AI increases demand for faster and more efficient computing. It pushes the development of cutting-edge technologies, as well as the related production and design capabilities, while creating higher barriers to entry,” said Bastianpillai.
Semiconductor equipment makers and software companies that enable semiconductor manufacturing should also benefit from the rise of AI, she added.
Allocating with care
In terms of allocations to AI-related companies, AB’s Berkow warns investors not to jump blindly on the bandwagon. “AI isn’t an end in and of itself; it’s all about the applications. The challenge is to figure out how AI fits into different industries and investment theses, by asking which companies will benefit and what types of jobs are at risk.”
More specifically, he believes that manual repetitive desk jobs that require little innovation are vulnerable, with chatbots already performing well when drawing from fixed information sets.
For the time being, companies that Michael White, global sector specialist, public equities at Schroders, describes as “picks and shovels” firms in the compute layer, look like winners, given their existing dominant positions.
Further, as generative AI use cases grow, he foresees demand for chips will grow too. “And NVIDIA is an expert with a dominant market share in the GPUs (graphic processing units) that are essential for AI processing.”
On the cloud side, the cloud computing market is an oligopoly. “At least for now, the big players like Amazon Web Services, Microsoft Azure and Google Cloud Platform will likely retain their advantage having invested significantly in infrastructure and established customer relationships in recent years,” explained White.
Meanwhile, although forward-looking companies might use AI to improve productivity, Berkow is concerned about declarations that AI will deliver real business advantages. “Companies that experiment and fail fast may actually find the best applications more quickly,” he added.
Sohn at Fidelity believes that consumer applications should enjoy earlier adoption than enterprise functions, given the data security/governance issues associated with AI applications for businesses, and the lower risk tolerance levels of businesses generally.
“We are seeing significant AI infrastructure build-out now but are very likely to see more volatility in this area over time as real demand will take time to materialise,” he added.
For now, Sohn sees companies spending to support AI rollout. “It should become clearer over the next 18 months or so whether businesses will start to accrue gains from this spending,” he explained.
