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Artificial Intelligence: Investor Considerations. Part II by Charles Schwab

Artificial intelligence is all the buzz with investors. But how do you evaluate AI companies, and what are the intrinsic risks?

https://www.schwab.com/learn/story/artificial-intelligence-investor-considerations

 

MIKE TOWNSEND: In 1999, the market was soaring. The S&P® 500 gained nearly 20% that year. But the tech-heavy Nasdaq went up an incredible 85.6%, driven by the trading frenzy that become known as the “dot-com” bubble.

It seemed like everyone wanted to invest in companies that had anything to do with the red-hot internet. Drugstore.com, Pets.com, eToys, and countless other companies—they couldn’t possibly miss.

An academic study found that just adding “dot com” to the name of a company in the late 1990s resulted in a 74% increase in the stock price over just 10 days.

But in March 2000, the dot-com bubble burst. It would take the S&P 500 more than seven years to get back to its high-water mark. It would take the Nasdaq 15 years to get back to its peak.

Most of the companies that soared in the 1998 to 2000 dot-com bubble are gone now. But some of the survivors are today among the biggest companies in the world.

In 2023, there’s a new term that’s attracting investor attention: “artificial intelligence,” or simply AI. Investors have been rewarding companies that are focused on AI, or even just companies that have AI in their name. Could this be another dot-com bubble? How can investors tell which companies have staying power, and which are just trying to capitalize on a buzzword?

Welcome to WashingtonWise, a podcast for investors from Charles Schwab. I’m your host, Mike Townsend, and on this show, our goal is to cut through the noise and confusion of the nation’s capital and help investors figure out what’s really worth paying attention to.

Today’s episode is the second of our two-part series focusing on artificial intelligence. In the last episode, I had the chance to talk with Bashar Abouseido, the chief information security officer here at Charles Schwab, about the rapidly changing artificial intelligence landscape, how companies are thinking about the future of AI, as well as the risks companies face with this technology.

Today, I’m going to focus on the investing side of AI. In just a few minutes, I’ll be joined by Randy Frederick, managing director of trading and derivatives at the Schwab Center for Financial Research, to talk about the opportunities and risks of investing in AI—and whether there’s a risk of a dot-com-like bubble.

But first a few updates on what’s happening here in Washington.

As expected, the Federal Reserve this week raised interest rates by 25 basis points to the highest level since 2001. It was the 11th rate hike in the last 16 months, taking the base interest rate, known as the fed funds rate, from near zero to a range of 5.25% to 5.5%.

But with inflation data continuing to trend downwards, the Fed is clearly nearing the end of this rate-hiking cycle. The question is whether this hike will be the last, or whether the Fed will feel it needs to increase rates one more time this fall. The Fed’s language following this week’s decision left its options open. The Fed Open Markets Committee does not meet again until September 19, so it will have nearly two months of additional economic data as it considers whether any more rate hikes are warranted.

Meanwhile, on Capitol Hill, Congress is trying to wrap up its work this week before its annual August recess. Lawmakers in both the House and Senate are making incremental progress on their biggest task—passing the appropriations bills that fund every federal agency and program for the coming fiscal year, which begins October 1. But “incremental” is the key word here. At best, the House hopes to have passed two of the 12 appropriations bills by the end of this week. And the Senate is likely to head into the August recess having passed each of the 12 bills through the Appropriations Committee, but not a single one on the Senate floor.

That sets up an epic time crunch in September. When lawmakers return to Washington after Labor Day, they will have just three weeks to pass all of those appropriations bills through both chambers, negotiate the differences between each pair—and those differences will be significant—and then each chamber will have to vote again on the consensus bills. It’s an impossible timeline to complete by the October 1 deadline.

That means Congress is likely to have to pass a temporary agreement to fund the government past the deadline while those negotiations continue—or risk a government shutdown. As I mentioned on the last episode, the House and Senate are writing their appropriations bills from different starting points—the Senate is using the numbers agreed to in last month’s debt ceiling deal, while the House is cutting more than $100 billion in spending from that agreed-upon number. How all of this gets resolved is anybody’s guess—and a government shutdown, whether it happens on October 1 or a bit later in the fall, remains highly possible.

Finally, there have been some notable developments on Capitol Hill in the effort to craft a regulatory framework for cryptocurrency. This week, the House Financial Services Committee is considering legislation that would give significant oversight responsibility for the crypto world to the Commodity Futures Trading Commission, or CFTC. It’s one of a trio of cryptocurrency bills that the committee is planning to vote on. But the bipartisanship that was hoped for in the House committee has slipped away, and the bills are likely to move out of the committee with little support from Democrats. There continues to be strong disagreement on Capitol Hill about whether primary regulatory responsibility should lie with the SEC or the CFTC.

At the same time, two senators, Cynthia Lummis, a Republican from Wyoming, and Kirsten Gillibrand, a Democrat from New York, recently re-introduced an updated version of legislation they first drafted last year that would also give regulatory authority to the CFTC. The bill would require all crypto exchanges to register with the CFTC and increase investor protections. While this bill is bipartisan, the same split over whether the SEC or the CFTC should be in charge exists in the Senate, making the bill’s prospects murky in that chamber.

And the SEC, which has stepped into the breach in recent weeks by suing the two largest crypto exchanges, Coinbase and Binance, suffered a legal setback in a court case against another crypto marketplace, Ripple. The judge in the case, somewhat confusingly, or at least to me, ruled that sales of XRP, Ripple’s cryptocurrency, to institutional investors violated the SEC’s rules, but its sales to retail investors did not. The SEC is expected to appeal the outcome.

All of this has created an uncertain regulatory environment for crypto that is evolving on the fly, resulting in confusion for investors, companies, and regulators alike. As 2023 began, there was real hope that cryptocurrency could be an area where the divided Congress could find some common ground and make real progress. Now, however, that looks less likely, meaning the uncertainty for crypto investors may continue quite a bit longer.

On my Deeper Dive today, I want to expand the discussion on artificial intelligence that we started in the last episode, where we looked at how companies are likely to put AI to use and the risks that come with such a transformational technology. Today we are going to focus on how investors should be thinking about the opportunities and the risks of investing in AI. To help me do that, I’m pleased to welcome Randy Frederick back to the podcast. Randy is the managing director for trading and derivatives at the Schwab Center for Financial Research. Randy, thanks so much for joining me today.

RANDY: My pleasure, Mike.

MIKE: Randy, I think it’s really interesting that artificial intelligence has been around for decades and most of us don’t even think twice about it. We use it every day—like when I ask Siri on my iPhone what the weather is or who won the World Series in 1967 or to find me a good recipe for chicken piccata. But it feels like AI burst into the public consciousness in a whole new way in just the past 8 or 10 months with the launch of ChatGPT and other tools that allow just about anyone to experiment with AI. At the same time, AI has become a dominant topic for investors trying to get ahead of what they see as the next investment opportunity poised for high-flying returns. There’s a lot I want to discuss with you today, but let’s begin by just getting your take on the state of AI right now.

RANDY: Well, I think the term “artificial intelligence,” or AI, like many things in technology, is a bit of a misnomer.

Computers currently lack the ability to actually be “intelligent,” though they can be programmed to simulate intelligence quite well. But learning, reasoning, and perception are very difficult to mimic.

Computers can easily be taught to do repetitive tasks, like reading, writing, talking, doing math, science, and history.

But computers can’t feel shame or guilt. They can’t have an entirely original thought. They can’t understand the concept of faith, read someone’s body language, or express their own opinions.

You can’t teach them to perceive, to rationalize, to empathize, to fear, to get angry, or to fall in love.

As you said, AI is not new, but it is a very broad and growing category, and it can include things like suggesting new music that you might like based on the music you’re already listening to; creating an investing portfolio based on your answers to a series of questions; intelligent virtual assistants that can answer simple questions online or over the phone.

Most of these things don’t impress us all that much. But the more natural language processing and generative AI products, which means they actually generate entirely new content, are rather impressive. Tools like ChatGPT and DALL.E 2, which can create songs, poems, stories, and artwork that looks or sounds like famous works, are what has really brought AI to the forefront recently.

As AI gets smarter, people will be freed from doing repetitive tasks, and they can focus their time and energy on things computers can’t do, or at least can’t do yet. Things that involve emotions, and creativity, and ingenuity.

MIKE: When you talk about people being freed from doing repetitive tasks, a lot of people hear that as the possibility that AI is going to take away my job, potentially lots and lots of jobs. How real is that worry?

RANDY: Well fears of being replaced by a machine are often completely justified, and it’s happened many times throughout history.

Back in 19th-century England, textile workers protested against cost-saving machinery that they said would replace skilled labor and produce inferior goods. They even took to destroying the machines, and I think we all know how that worked out.

In history there are many examples of innovations that completely eliminated their predecessors—and now we can’t imagine it any other way:

I mean slide rules were replaced by calculators, typewriters by word processors, telephone operators are essentially gone—in fact, very few people even own landlines these days. Horse buggies lost out to cars, and now gasoline cars are slowly losing out to electric cars. Newspaper reporter jobs are declining, and newspapers are nearly gone, replaced by digital media.

As AI evolves, there will be many jobs that will be made obsolete, but new jobs will be created, and many of them will be in areas that don’t even exist yet.

It’s like how the growth in renewable energy meant many jobs were lost in the oil fields over the last decade, but many more have been created as the need for solar panel installers, people who climb up and maintain giant wind generators, and a variety of other jobs has exploded.

Consider that in 1990 there were about 800,000 information technology, or IT, jobs in the U.S.; today that number is over 4 million. That represents 3% of all jobs, and the annual growth rate is also about 3%. I think it’s safe to say this will only accelerate as AI grows and proliferates.

While many of those jobs will require a different skillset, there’ll be plenty of opportunities for those willing to adapt.

MIKE:  That’s a great point—while AI may make some kinds of jobs obsolete, it’s going to open up whole new areas of jobs that will likely see enormous growth, because after all, it’s humans that will program AI and figure out how to use AI.

But we also know that advances don’t usually treat all areas evenly—there are always winners and losers. So what kinds of jobs do you see going away, and what kinds of jobs do you see expanding as a result of this technology?

RANDY: As we talked about earlier, computers are very good at repetitive tasks, and nearly all occupations involve some activities that are repetitive.

Jobs that are already on the decline include manufacturing jobs, replaced by automation; first level customer service roles, replaced by virtual assistants; even the people who support doctors and lawyers often spend an enormous amount of time filling out insurance forms and creating boilerplate contracts that are already being automated.

Within the IT sector that we just mentioned, there will be many more people needed in robotics and automation, and to teach the machines how to speak, how to learn, how to create, and, perhaps most importantly, simulate empathy and avoid biases.

AI has the potential to improve efficiency and productivity in nearly every industry.

And while many of the new jobs will involve a level of technical expertise, IT jobs generally pay far better than manufacturing or clerical jobs.

MIKE: While there are a lot of people who are excited about some of these opportunities you are describing, there are also a lot of people who are afraid of AI. I guess we’ve all seen too many movies about the machines taking over the world. What do you say to ease concerns of people who are afraid of some of these changes that are coming?

RANDY: Well, obviously, some people fear that with AI, computers might become smarter than we are. I’d argue that in some areas they already are, and they have been for decades.

I mean, I can’t calculate a square root to 10 digits in 1 second, but I’ve got a 30-year-old TI calculator that can.

I can’t tell you who sings that song, but Shazam will recognize it in about 10 seconds.

I can’t tell you how to avoid traffic on your way to the restaurant, but Google Maps gives it to me in like 5 seconds.

But computers still can’t build themselves; they can’t program themselves; they can’t even provide power to themselves, not yet.

I believe AI will change our lives in the next 30 years as much as the internet has changed it in the past 30 years.

Just as every business in the world has been impacted by the computer age, by the internet, and especially by social media, so too will they all be impacted by AI.

But we shouldn’t think of AI as a replacement for anything, but rather as an enhancement for everything.

AI will improve things we can’t even imagine today. I mean consider what you thought about the internet back around 1993.

Did you think back then that you’d be paying bills, dating, banking, shopping, traveling, navigating, communicating, investing, attending college, visiting a doctor, watching TV—did you imagine that you’d control your garage door or thermostat or keep an eye on your front door all online?

Technological advancement can never actually be stopped; it can only be slowed down. But even that has risk because if we slow it down here, it’s a sure bet that other countries won’t.

AI is one of those topics that causes fear in some people, mostly because they’re a little too focused on the negatives. But there will be some. Indeed, there are already deepfake videos of people saying and doing things they never did. There are new songs being sung by performers who are no longer with us. There are brand new Picassos being created 50 years after his death. We can no longer trust our own eyes and ears; we’ll need to be more diligent in every way.

One very promising area, but also a challenging area for AI, is in self-driving vehicles.

Years of research indicate that about 90% of all automobile crashes are the result of human error.

And while autonomous-driving technology still has a long way to go, there’s little doubt that eventually AI will substantially lower that number.

And think about how autonomous driving will improve the mobility of the elderly and the disabled.

MIKE: Yeah, Randy, this balance between the advantages and the potential dangers, I just think it’s going to be so interesting to watch. Just last week President Biden met with executives from seven major AI companies including Google, and Meta, Microsoft, and OpenAI, which is the company behind ChatGPT. And they agreed to a set of voluntary standards and safeguards. But whether those will be effective and potentially more broadly implemented, I think it’s far from certain right now. Well, let’s change gears, Randy, and look at this from the investor’s point of view. I ‘m an investor, and I want to take advantage of the changes that AI is bringing. What kinds of businesses should I be looking at?

RANDY: I think it’s safe to say that companies who embrace and exploit AI will likely thrive; those who shun, avoid, or fear it will likely suffer.

There will be companies that profit handsomely through the use of AI, but the greatest opportunities may lie with those who create it, who license it, and who sell it.

I’ve used this analogy on your podcast before, Mike. As you know, when the gold rush hit California in the mid-1800s, it wasn’t most of the gold miners who struck it rich. Sure, there were a few, but the real money was made by those who sold picks, shovels, and blue jeans.

And when it comes to AI, I think the first and probably the most obvious examples of this are in the computer chip makers.

As with any industry, there will be leaders whose chips are preferred by those who produce software, automation, and other products, but sometimes the best can be very expensive.

So at the same time, there may be other chipmakers who can produce reasonable substitutes at a much lower cost.

Likewise, there will be companies that develop smartphone apps and innovative software that employ AI capabilities. Software-as-a-service, or SaaS, is already a $300 billion industry, and it’s growing at a rate of about 20% per year.

An important point I’d like to make here is one that investors sometimes tend to overlook. Often the first use of the most cutting-edge technologies will appear in the entertainment and gaming industry.

Facial recognition, voice recognition, gesture control, cloud computing, virtual and augmented reality, and wearables are all good example of this. They all started with gaming, but later found, or are currently in the process of finding, mainstream applications.

So even if you’re not a gamer, good ideas can sometimes be found by thinking about how the newest gaming technology or entertainment tool might be used in everyday life or in business.

MIKE: You know, Randy, to some investors this is starting to feel like the dot-com bubble in the late 1990s. So what are some lessons learned then that could apply now as investors watch this new trend start to unfold?

RANDY: This is where investors are going to need to do a little of their own homework.

First, we need to be especially diligent to weed out the real AI companies from the wannabes. We need to distinguish between those who use AI and those who help create it. And perhaps most importantly, those who talk AI and really don’t have anything to do with it.

I would be especially cautious of those who say that they’re working on it—either developing it or adding it to their existing products. Don’t take their word for it. Do some research. And not on chatrooms and social media sites, but from reputable sources such as those whose research we make available on Schwab.com.

During the internet bubble, it seemed like every company added .com to their name just so people would notice them. Of course that didn’t mean they were a technology company. It simply meant they had a website. Today everyone has a website.

As you said, the corporate graveyard is littered with names from that era such as Pets.com, Boo.com, Webvan, eToys, GeoCities, TheGlobe, InfoSpace, and on and on.

AI is kind of in the early stages of something similar. As I said, virtually all companies will use AI, but a much smaller number of them will actually build it.

MIKE: You know we’re already seeing attention being paid to companies that have AI in their names. So how do investors avoid those mistakes this time? I mean it can be hard to do when you are excited about something—and especially if you think you can make a lot of money very quickly if you pick the right horse.

RANDY: Well, don’t assume that a company that talks AI is really doing AI. Don’t get derailed by the fear of missing out, or FOMO. And don’t believe everything you read unless you can verify that it’s from a reputable source.

Another important piece of advice that’s as old as investing itself: Don’t put too much into any one company.

While a well-diversified portfolio is unlikely to result in a 100% or greater annual gain, it’s also probably not going to result in a 50% or greater loss.

At Schwab we always recommend a proper asset allocation plan and a long-term perspective for the core of your portfolio.

If we step back for a moment to the .com era and focus on those companies that not only survived but thrived—so, for example, Amazon, Google, eBay, Qualcomm—the greatest returns on all of them would have been realized by those who held them for the long-term.

And if there’s a small company that you have a good feeling about, there’s nothing wrong with putting a little speculative money into it. Just make sure that it’s a small amount of your portfolio, and that it’s money you can afford to lose.

As we’ve discussed, AI isn’t new, but it is becoming more and more sophisticated; and future capabilities are hard to even imagine.

MIKE: Well, Randy, you’ve really emphasized education, so what are some practical steps investors can be taking now to get themselves more educated?

RANDY: Be sure to research companies from reputable research organizations.

Schwab clients can go to Schwab.com, where they’ll find not only Schwab Equity Ratings (or SER) reports for many companies, but also third-party research from companies like Morningstar, Thomson Reuters, CFRA, Argus, Vickers, MarketEdge.

And pay attention to how companies differentiate themselves from competitors, and whether or not their products or services can be easily duplicated.

And like any company, watch how quickly they burn through their venture capital or how fast they’re growing their revenue.

Making a lot of money very quickly by picking “the right horse” as you suggested is not really investing—that’s gambling.

Investing is not about getting rich quick; very few people are fortunate enough to do that. Investing is all about getting rich slowly; and most people are capable of doing that, as long as they’re careful.

And if you need help, I would encourage you to make an appointment with your financial consultant.

MIKE: Well, as always Randy, great advice. And this time about a topic I think is really on the front of a lot of investors’ minds. So thanks so much for joining and sharing your perspective today.

RANDY: Always a pleasure, Mike.

MIKE: That’s Randy Frederick, managing director for trading and derivatives at the Schwab Center for Financial Research. You can follow him on Twitter @randyafrederick.

That’s all for this week’s episode of WashingtonWise. We are going to take a break for August, so we will be back with new episodes in September. Take a moment now to follow the show in your listening app so you don’t miss an episode. And if you like what you’ve heard, leave us a rating or a review—those really helps new listeners discover the show.

For important disclosures, see the show notes or schwab.com/washingtonwise, where you can also find a transcript.

I’m Mike Townsend, and this has been WashingtonWise, a podcast for investors. Wherever you are, stay safe, stay healthy, and keep investing wisely.

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