AI is coming? No, it’s already here.

Artificial Intelligence (AI)
AI is coming? No, it’s already here.

March 28, 2024

2023 will go down as the year when Artificial Intelligence (AI) became omnipresent in the lexicon of society.  Companies at the forefront of the AI revolution dominated the headlines and outperformed the broader market. In Q4 2023 earnings calls, 36% of S&P 500 companies mentioned “AI”, up from 31% in Q3. That trend is likely to accelerate during upcoming Q1 2024 earnings calls, considering that companies mentioning AI during Q4 2023 posted an average stock price increase of over 28% last year.

For investors, the challenge in navigating the AI euphoria lies in separating the hype from the reality, and there are potential gains to be had for those who can think outside the box and identify overlooked areas where AI technology can be applied. But what exactly is AI, and can it deliver on promises and hype?

For most people, the term evokes thoughts of science fiction movies in which computers or robots achieve a degree of sentience, reaching or even exceeding human intelligence (and frequently going rouge, à la 2001’s HAL or The Matrix’s Agent Smith). The reality is that AI in its present state is more akin to an open-ended computer program. AI mimics human learning in identifying patterns, making predictions, and analyzing results and applying prior successes and failures towards constant improvement.

AI is already here, and you already interact with it, possibly without even realizing it. The predictive text on your smartphone (and Microsoft Word, which finished that sentence as it was being typed) is a form of AI. The (possibly frustrating) customer service agent you chatted with on an e-commerce website was possibly AI and if not, it soon will be. Did you unlock your phone by using facial recognition? That was AI again. There are countless other examples, such as the movies that Netflix (NFLX) suggests, the stories and posts on your Facebook (META) feed, and the traffic alerts that show up in Google (GOOG) Maps.

These relatively mundane, everyday use cases are often overlooked amidst the excitement over more futuristic sounding promises of automated vehicles, robotic factory workers, and neural implants that could increase human brainpower. While we are rapidly progressing towards those three examples, the next stage in AI is likely a widespread adoption beyond traditional tech companies by other industries.

One of the most obvious and exciting applications for AI is the potential to accelerate scientific and medical research. AI can potentially speed up pharmaceutical development and testing, by identifying optimal chemical compounds and making predictions on the efficacy of drugs in development. AI can assist in cataloguing and drawing conclusions over drug performance and side effects and possibly identify potential adverse effects in advance – drugmakers such as Pfizer (PFE) have used AI in this capacity for roughly a decade already.

Outside the healthcare sector, retailers of all types are beginning to apply AI to analyze customer behavior, processing massive amounts of real-time data on buying patterns, finding optimal pricing, and managing inventory. Much to the chagrin of music and sports fans, ticket-sellers such as Ticketmaster (TKTM) and StubHub have implemented AI to apply dynamic or “surge” pricing algorithms that automatically raise prices to coincide with peak demand.

As AI continues to improve and evolve, humans will no longer be required for several jobs, and the technology will augment human workers in even more roles. Customer service, data entry, and telemarketing roles are already being replaced and AI can also be trained to handle less-complex computer programming and coding tasks. Presently, machines are responsible for 34% of business tasks, but that percentage is expected to grow to 43% by 2027 according to a World Economic Forum study. Thankfully, at least a portion of the job losses will be offset by the need for more data scientists, engineers, robotics experts, and other highly skilled roles.

As investors, there are several ways to position portfolios for the coming AI revolution. The simplest would be to stay the course and maintain market-cap weighted exposure to the US economy. The US is at the forefront of the AI revolution and the technology will permeate through all economic sectors as already mentioned. The successful companies will see the biggest share price gains and therefore hold larger weight in the market-cap indices (as has been the case for Nvidia, which has grown from $200 Billion to over $2.2 Trillion in just 5 years). In 2023 we saw this play out, as the “Magnificent Seven” mega-cap stocks – all of which have significant AI exposure – accounted for a disproportionate amount of the S&P 500’s return.

For investors looking to be more aggressive, allocating more heavily to the Nasdaq or the S&P Technology Sector ETF (XLK) is a way to increase AI exposure. While Tech won’t be the exclusive beneficiary of the AI boom, the chipmakers and cloud data storage operators are essentially the nuts-and-bolts of AI and still have plenty of runway despite their incredible recent performance. There are also specialized ETFs available focusing on AI, such as the Invesco AI and Next Gen Software ETF (IGPT), or the Global X Robotics and AI ETF (BOTZ).

To position portfolios for the “second wave” AI boom, in which non-tech companies integrate and apply AI technology to improve margins and accelerate growth, investors should look to identify companies that are financially healthy to engage in cap-ex spending. With interest rates still elevated, companies with healthy cash flows and a track record of spending on R&D will obtain a first mover advantage on building out their AI strategies. Screening the Large Cap universe of stocks for those with highest ratio of R&D spending to Revenue yields non-tech companies such as Deere (DE), Johnson & Johnson (JNJ), and Schlumberger (SLB). Expanding the search into Small- and Mid-Caps reveals companies such as medical device maker Edward Lifesciences (EW), chemical maker FMC Corp (FMC), and glassmaker Corning (GLW). Even newspaper publisher the New York Times (NYT), which sued Microsoft and OpenAI over ChatGPT’s tendency to plagiarize its content, recently announced plans to hire AI-specialized staff. While there is no guarantee that these companies will successfully integrate AI into their respective businesses, identifying firms willing to spend on R&D may be a way to find the next, less-obvious beneficiaries of the AI revolution.

AI is looking less like a dot-com bubble 2.0 and more like a revolutionary breakthrough that will unlock efficiency and alter the way companies do business in years to come. AI is already spreading beyond the technology sector and in a few short years, will likely be a universally necessary strategic initiative across all major industries. Investors can capitalize on the AI boom by looking beyond the obvious beneficiaries and positioning their portfolios on the crest of the “second wave”.

Read the Forbes article – Here

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