The age of AI and its long-term investment potential

Key points:

• Technology stocks are dominating equity markets once again chiefly because of the recent rise, and long-term potential, of artificial intelligence
• Many believe AI’s impact on the world and global economy - especially that of generative AI - will be hugely significant
• For growth investors, we believe AI offers strong opportunities to benefit from potentially superior earnings growth

Technology is once again the dominant story in equity markets. While the S&P 500 is ahead by some 19% year to date, the tech-heavy Nasdaq index has delivered a formidable total return of 35% as behemoths such as Amazon, Alphabet, Microsoft, Apple and Google have seen their shares prices soar.¹

Central to this rebound - following the sector’s period in the doldrums during 2022 - is the recent rise, and perceived long-term potential, of artificial intelligence (AI).

It has been a topic hard to miss in 2023 - notably 110 constituents of the S&P 500 mentioned “AI” during their first-quarter earnings calls, the highest number in more than a decade.²

Behind the current ubiquity of AI is ChatGPT. Launched in November 2022, it instantly captured the world’s imagination; the inception of the conversational AI engine marked a significant milestone in presenting a consumer-friendly aspect of the innovation. Such was the level of interest in the service, it took just five days to reach one million users³ before crossing the 100 million user mark in January 2023.⁴

But the reality is AI is already pervasive and it has been for some time. Algorithms dominate our life, from the music and movies we stream, to what’s recommended when we go shopping online, and much, much more. As such, there are considerable investment opportunities in both the design and infrastructure of AI but also across a broad number of sectors as companies in different industries begin to use AI to improve their own business models.

What is AI?

At its most basic AI is simply about machine learning, i.e. a computer’s capability to think and learn – to perform tasks and cognitive functions we usually associate with human beings. AI programmes can learn, via data gathering from large language models and establishing rules – algorithms - by which they operate and use this information to understand how to deal with the information they have e.g., Spotify, Netflix et al.  AI can also reason – deciding on algorithms – to choose outcomes, and correct information.

AI comes in several subsets. For example, familiar household, and handheld, virtual assistants like Amazon’s Alexa or Apple’s Siri are subsets of machine learning, where a neural network attempts to simulate human knowledge acquisition – this is done by creating algorithms which are trained to learn from experience. Deep learning is a subset of machine learning, which involves training neural networks that mimic the structures of human brains. Neural networks typically have multiple layers and can be trained to perform specific tasks such as image or speech recognition - examples of deep learning include facial recognition and the work going on in driverless cars.⁵

Generative AI, such as ChatGPT, takes all this much further. It can create and produce text, images, video, and numerous other types of content – as such its potential to disrupt a vast range of industries is immense.

The growth potential

Many believe AI’s impact on the world and global economy - especially that of generative AI - will be of seismic proportions; it can help automate tasks, such as dealing with customer queries, in turn freeing up workers to focus on more strategic and complex tasks, significantly increasing productivity. Consultancy McKinsey & Company believes this could add trillions of dollars in value to the global economy as generative AI could potentially automate activities that presently take up some 60% to 70% of workers’ time.⁶

For its part PwC has described AI as the “biggest commercial opportunity in today’s fast changing economy”.⁷  The group believes it could contribute a massive $15.7trn to worldwide GDP by 2030 and that there could be a 26% boost to local economies from AI over the same period, with China and the US likely to enjoy the biggest GDP gains.⁸

As for the AI market’s growth potential, one analysis forecasts that its current value of some $100bn could grow twentyfold by 2030, up to nearly $2trn.⁹  But while there is a lot of buzz around AI’s potential in the short term, this is very much a long-term productivity story which will likely reach across sectors. The initial introduction of computers in general – and subsequently the internet age - saw productivity accelerate. AI marks another seismic step change in the digital era.

In another AXA Investment Managers’ Investment Institute paper, we consider the economic implications of widespread AI usage.

And although we believe AI, given its vast potential, will be a vital thematic investment story over the coming decade - and beyond - its impact will be incremental.

Right now, cloud computing, data centres, server and computing capacity, as well as semiconductors and semiconductor equipment companies, are among the immediate potential winners of generative AI, as more computing, memory and networking solutions are required for computer processors, graphics processing units, and other specialised equipment.

Chipmaker Nvidia became a member of the select club of trillion-dollar companies, as demand for its graphic processors which train AI systems, rocketed this year.¹⁰  Another chip manufacturer, Marvell Technology, has also witnessed strong share price gains in the wake of an upbeat earnings report, driven by the excitement engulfing the AI sector.¹¹

Beyond infrastructure

Everything from supply chains, marketing, analysis, and more will embrace AI over the coming years. Banking, high tech, and life sciences are among the industries that could see the biggest impact as a percentage of their revenues from generative AI.¹²

The current focus on infrastructure will expand over time into those companies creating applications – and the possibilities here are arguably endless. It will help improve healthcare – from diagnosing diseases and developing new treatments and improving patient care. AI can improve energy efficiency and help develop new technologies to deliver more sustainable energy. It can enable greater efficiency and safety in transportation – from electric vehicles to improving traffic flow.  

Already we are seeing software-based client relationship management firms such as Five9 and Salesforce adopting AI while services companies such as Accenture, Capgemini and Globant are involved in the development of applications around AI being spearheaded by the larger players including Amazon, Microsoft and Alphabet. Among the developments is Google’s spate of new generative AI powered features including its Search Generative Experience and a new large language model (LLM) to power its chatbot.¹³

And it’s not just tech firms wanting to get in on the action. Since its theoretical birth in the 1950s, more than 340,000 AI-related invention applications have been filed. But over the past decade, this has rapidly accelerated from 2,560 patents in 2010 to over 140,000 in 2021.¹⁴

This should raise some caution, of course, as not every AI innovator will be a success and certainly the hype around AI will bring back memories of the dotcom boom and bust at the turn of century. But in our view today’s wider technology sector is a very different beast; back then, in several cases, company valuations were based on aspirations rather than anything fundamentally tangible. Today companies have very real clients, revenues and profits. There will be AI winners and losers, and while right now, many firms are reaping the benefits of the current wave, it is too early to assess what the environment will look like in five, let alone 20, years’ time.

The digital road ahead

There will be issues to be resolved and scrutinised, as there are for all new areas of technology, for example security, accuracy and consistency. Regulation will be a key factor here and already the European Union is developing an AI Act to “to ensure better conditions for the development and use” in a bid to protect companies and consumers.¹⁵

But given the excitement we have seen to date, the velocity to reach commercialisation may be swift, especially as there are many users around the world who are ready to use this format of the technology.

Any consumer who is already comfortable talking to their Alexa, Siri, Google Assistant or Roku smart TV is already well versed in what it takes to use a conversational AI user interface – and this should only speed up adoption. This underlines the structural changes we are already seeing; changes that are supporting the adoption of AI and bolstering its long-term investment potential.

For investors, particularly those with a bias towards growth equities, AI offers tremendous potential opportunities to benefit from superior growth in earnings. At the same time, there will be companies that lose market share if they fail to fully exploit the opportunities offered by more powerful computing power. In developed countries facing demographic challenges and labour market constraints, the power to automate various economic activities and to deliver services and goods to consumers using AI techniques will have revolutionary economic and social implications. We believe this will be a dominant investment theme for years to come.

References to companies are for illustrative purposes only and should not be viewed as investment recommendations.