Investing in AI – how to gain exposure to the macro trend set to turbo charge productivity

by Jonathan Adams
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The late 2022 public release of OpenAI’s ChatGPT large language model (LLM) has triggered an AI arms race. Alphabet-owned search giant Google also unveil its own LLM app – Bard. And other tech giants including China’s Alibaba have reacted and debuted their own comparable user-facing AI apps.

These AI chat apps, trained on large swathes of the internet but still generally unable to access it in real time, have impressed and perturbed users and observers. Their ability to understand free-text questions and commands and return written responses that sound close to human is impressive.

Applications range from crafting emails to the ideation and outlining of articles, speeding up the research involved in their writing or summarising key points within a large body of text. Tools with more specific applications, powered by the APIs of LLMs like ChatGPT are also already appearing. Examples include Microsoft-owned GitHub’s CoPilot, which helps programmers write code, and the restaurant booking ChatGPT plugin OpenTable.

Wherever you stand on the spectrum of how revolutionary the flood of AI tools and products that will come to market over the next couple of years and beyond will prove, there’s little doubt they will have an impact. The only real question is how big that impact will prove in the shorter term.

Many see parallels with early days of the internet and the possibility of both big changes to existing products and services newly infused with AI and entirely new and as yet unimagined technologies and business models made possible.

Some believe that the next generation of “mega-cap” tech giants will emerge from the pipeline of AI startup IPOs that will take place over the next few years. And that the AI revolution will also result in winners and losers among today’s titans of tech.

Investors are trying to guess how much of a lift existing tech companies might get from the launch of new AI products, or its integration into existing software like Microsoft’s Office365 productivity suite. They’ll also be trying to spot the new AI companies that will become giants early.

Why much of the value generated by new AI is likely to be swept up by incumbent big tech and not new arrivals

The next major cycle of venture capital and private equity investment in startups will almost certainly have a strong focus on AI. However, it’s still not clear if the technology will open up a significant number of brand new markets of the kind that could give rise to new mega companies like the internet giants that include Amazon, Meta and Alphabet.

Until now, most of the value of innovation in machine learning, the broad category of AI that LLMs like ChatGPT belong to, has been swept up by the incumbent big tech companies. It has been more about deploying it to the benefit of existing customers, products and business models. The ChatGPT app itself, a premium subscription that guarantees access to the latest version released even at peak times costs $20, is one of the few examples of a brand new and directly revenue-generating AI product.

However, a leaked memo from Google itself called into question if any company developing LLMs and other AI can realistically claim to have a meaningful IP ‘moat’ against the competition. Open source LLM code bases that can be further refined and trained on new data are readily available and, said the leaked Google memo, can relatively easily be brought up to the standard of ChatGPT and Bard, especially for narrower applications.

There will undoubtedly be a wave of profitable products and use cases that leverage LLMs but they are likely to be narrowly focused, at least initially, and not provide the platform for AI start-ups to reach valuations in the hundreds of billions of dollars.

But the companies already worth hundreds of billions of dollars will leverage AI in ways that could further boost already huge revenue streams and help cut costs. That will add value for shareholders.

Cloud computing platforms such as Amazon’s AWS, Microsoft’s Azure and the Google Cloud Platform, and chip makers like Nvidia and Micron, are likely to be among the most significant beneficiaries of the LLM wave that will require huge amounts of computing power. They have already swept up most of the value created by AI innovation so far.

The early stages of AI innovation have yet to produce a new public company or private unicorn, that looks like it could have the potential to become the Google or Amazon of machine learning. That includes OpenAI, whose early-starter competitive advantage already looks vulnerable to erosion, long before it has reached profitability.

How to invest in AI – should you look for increased exposure to incumbents or take a risk on startups?

The Economist’s Buttonwood column concludes “it is possible an investment in a broad index fund tracking existing listed tech firms will end up outperforming the equivalent investment in private, strictly ai-focused startups.”

Another risk with investing in AI startups is the amount of hype around the technology, based on historical precedent of frothy new sectors, likely to lead to over-valuation. Many, if not most, of those startups will fail to live up to the hype and expensive-looking early valuations.

There may, however, be interesting opportunities for investors around companies that are neither pure-play AI startups nor among the tech giants but do have existing successful tech businesses that AI will boost. The valuations of these companies have not already been caught up in the AI hype but stand to benefit from the technology.

The Motley Fool highlights two stocks that fall into the latter category – the data centres REIT Equinix and Intuit. The latter owns a portfolio of SaaS products for SMEs that included the accountancy software QuickBooks and MailChimp, the email marketing tool.

Equinix CEO Charles Meyers says the company’s data centres are already seeing growing demand from companies that need to store the data used to train and run generative AI programmes. While he calls it “early days” for AI-driven data demand, he sees it as an “exciting incremental opportunity for the company”.

Equinix already offers a 1.9% dividend and has a record of steadily increasing it over time. AI could support strong occupancy, rising rental rates, and new development opportunities for the company, which will subsequently benefit shareholders through a growing dividend, capital growth, or both.

Meanwhile, Intuit is infusing its existing SaaS products with AI, improving them for users in a way that will hopefully both increase their market share from competitors and allow them to command higher prices. Quickbooks already uses AI to support customers with automated digital assistance and Mailchimp users benefit from AI that can automate, generate, and optimise content, saving time and improving outcomes.

Intuit currently pays a modest dividend of 0.7% after raising it by 15% this year. That does leave plenty of potential for dividend growth though and the company has a track record of regular increases, despite being the kind of growing tech company that usually doesn’t pay cash out to shareholders.

Beware the hype when investing in AI

Savvy investors will undoubtedly benefit from AI innovation but that will necessitate carefully sidestepping the hype and avoiding over-valued startups. There will be AI startups that will go on to be successful but the chances are many more won’t, just like the companies at the vanguard of any major new technology, like the internet was 2-3 decades ago.

Higher net worth investors might consider AI investment opportunities in riskier startups, especially through tax-incentivised schemes like EIS and SEIS. However, there is doubt about how much potential there is for these companies to evolve into new tech giants comparable to the incumbent internet economy giants.

Much of the early value is likely to be realised by companies that already exist and are profitable today. And that’s where private investors with less racy risk profiles should look.

Disclaimer: The opinions expressed by our writers are their own and do not represent the views of Trading and Investment News. The information provided on Trading and Investment News is intended for informational purposes only. Trading and Investment News is not liable for any financial losses incurred. Conduct your own research by contacting financial experts before making any investment decisions.

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