Artificial Intelligence: The Next Technological Tectonic Shift?
- 16 mins 15 secs
In this podcast, equity portfolio manager Brad Mak and Rob Almeida, global investment strategist, discuss how the commercial application of artificial intelligence may affect - enhance, be neutral to, or detract from - companies over the next three to five years.Channel: MFS Investment Management
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Welcome to another edition of the Strategist's Corner podcast. I'm your host, Rob Almeida, MFS Global
Investment Strategist. This episode focuses on AI, and I'm thrilled to be joined by MFS US and Global
Large Cap Growth Portfolio Manager, Brad Mak. Our discussion will focus less on the science behind
artificial intelligence, or language learning models, and more on the commercial application of the
science, and how it impacts stocks.
Profits drive stocks, thus how this new technology will impact how companies run their businesses will
be ultimately what matters, what revenue streams are at risk, what costs can be taken out, what
productivity may be gained, and how all this ultimately affects profit and loss statements. I hope you
The views expressed are those of the speaker and are subject to change at any time. These views are for
informational purposes only and should not be relied upon as a recommendation to purchase any
security or as an offer of securities or investment advice. No forecast can be guaranteed. Past
performance is no guarantee of future results.
Thanks for having me, Rob.
Starting at a high level, what are you hearing from companies? How are they talking about AI, and then I
guess most importantly, how are you and the investors thinking about AI in your portfolios?
That's a great question. I think just at 30,000 feet, I think the consensus is this is a tectonic shift in
It's akin, you've heard it mentioned multiple times to the creation of the internet, the invention of the
mobile phone. Anytime there's a big pivot in a technology platform, there's always more questions than
answers. I would just say right now, there is a bit of a frenzy. It feels very similar to 1999, 2000 where
every company attached dot-com, the early 2010s, where every company said they were a cloud
company, every company's narrative is now how AI is going to help them.
From our standpoint, our job is really to sift through that noise and understand how this is going to
impact industries and companies over the next three to five years. What we've been trying to do is really
think about every industry and company, just where is it most obvious where companies are going to
win, which companies, industries where it's at least neutral, if not going to help them, and then more
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importantly, which companies potentially are going to be at risk from a business model, profit, margins,
all of that?
Yeah. Let's talk about category three. A couple years ago or earlier when we were doing these podcasts,
CV Rao, who you know very well and worked closely with, was a guest, and he talked about Internet 1.0
or Web 1.0 companies, which you referenced earlier, then Internet 2.0, and then ultimately, Web 3.0.
His point was, what resonated with me, and I think a lot of the listeners, was 75% of the companies that
exist currently, call it the Web 2.0 era today, didn't exist back then.
Sort of the Schumpeter creative destruction innovators get innovated. That company three or that
category three category, without mentioning any names, is there any maybe obvious points, or obvious
relative industries or anything like that that you can share with us?
Yeah, so I think what we're going to see over the next three to five years is companies that were formed
over the last 10 to 20 years have incumbent profit pools that they need to defend, and they're going to
look for ways to use AI to help at least protect that, and then try to augment it. What we saw coming
out of the internet era and the mobile era is there will be hundreds if not thousands of new companies
funded. Most of them will not scale, but a handful probably will come that we are not thinking about
What we're trying to figure out is what does AI do? It really is a set of computer programs that helps
make things more efficient, workflows, repetitive tasks, and it's getting more and more intelligent. We
are just thinking about businesses that charge per seat, or rely on labor as their business model. We're
not sure in the near term, but in the long term, there are questions. There is deflationary pressure on
labor, does that just mean less seats to sell to with a software based business model?
If your business is hiring people to implement outsource services, if some of that gets automated away,
what does that mean for your business? How are you going to pivot?
Yeah. Then it just comes back to blocking and tackling. What does a company do? How do they do it,
and can they keep doing? What's the durability of that? Is that, sounds like that's what you're talking
100%. We're always focused on what is the rate of growth, and the duration of growth of a business,
and how durable is that?
Right. That rate of growth is obviously a function of value proposition. If that value proposition is now
being duplicated by AI, LLM, whatever it might be, that revenue stream goes away.
That's right. If you take a generic enterprise software company today, they sell some sort of software to
help automate a workflow. They are introducing AI features and functionalities somewhat like a co-pilot,
and they want to charge more for that.
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We don't know how much the customers will be willing to pay for that, probably something for the
productivity enhancement. On the flip side is if your Fortune 500 company says, " we don't need 5% of
our headcount anymore, because it's getting audit in May," that is a headwind offsetting a potential
tailwind. We don't know, is that neutral, is it positive or negative? These are the questions we're asking
company by company within each industry on the implications.
Yeah. Maybe this is an out of bounds question, but taking a step back, so coming out of the global
financial crisis, central banks took rates to zero, quantitative easing. You had an environment where a
lot of businesses were fungible, just because capital costs were so low. Maybe some of these companies
that came out of it were at risk. Just at a high level, it just seemed like so much capital was divested from
physical assets, plant, property, equipment, into, let's call it intangible software, et cetera.
Almost now, it just seems like we're flipping the script. Supply chains are shortening. You have industrial
companies that sell parts and services to help companies reduce greenhouse gas emissions, et cetera.
That capital has to come from somewhere. Maybe if I'm putting these two things together here, we
have an environment where rates are no longer zero, those companies might not be fungible. Now, you
add in this dynamic that you're talking about, with AI possibly duplicating their revenue streams. Is that
I think it's a fair set of observations and questions, and I see it as two parallel drivers of secular growth.
A lot of the hard asset type topics you brought, on-shoring, re-shoring, strengthening supply chain, that
has to happen from a supply chain resiliency, from a national security, from a just geographic diversity. It
has to happen. AI has to happen. The ship has sailed. If you are a company facing potential disruption,
and you do not invest in an AI roadmap, you will eventually be disintermediated.
It is table stakes. What we saw the last decade was just low rates, free money, and we saw a lot of
businesses that were funded in FinTech and biotech. A lot of that has evaporated, but there's still a lot
of dry powder sitting at VCs and PE firms, and they are funding this next wave of AI companies.
Right, right. Let's go back to category two, so companies that maybe on the neutral end, that whether
they are levered to AI, from the standpoint of they're selling products or services alongside that, or
maybe it's companies that are benefiting because they're getting more productivity. How are you
thinking about that bucket?
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I think it's a broad bucket and it's constantly evolving, literally week to week, month to month,
depending on what companies are communicating about their AI strategy. As investors, we historically
have always tried to lean on the suppliers or the picks and shovels that are providing the required,
whether that's the capital, or the compute, or the hardware, or the semiconductor tools required to
enable this. That's where we focused on at least neutral to positive.
Then as we move up the stack, there's a broader set of questions where you can't just make a broad
statement. This is good or this is bad, it is company specific. This is where active management comes in.
This is where a global research platform comes in. This is where interviewing companies, doing
comparisons across geography really matters to sift through and figure out, who has the right roadmap?
Where does it make sense where they're going to win, versus those that are just sort of putting out a lot
of press releases where there's no substance there?
As all these companies, all these tech companies, are talking about AI and delivering a value proposition,
are there ways to channel check? You have to take them at their word, and ultimately, you want to see
it through the income statement, but are there ways to learn that? Who has a competitive technology
that will be commercially successful?
Yeah, it's a great question, and I'll give you some real time examples of what we've been doing at MFS.
We've had not only companies that are perceived winners, where we're talking to the companies, you
see it in the numbers today, but it's the companies where we have questions about category three.
Well, what are you doing? How are you thinking about it? How will this actually benefit you? We are
talking through industry channel checks around that.
We're talking to old line companies that historically, maybe wouldn't have participated in this
technology shift, and asking them, "What is your AI roadmap? How is this going to implement and
maybe change how you run customer service, or product development in healthcare and life sciences?"
That creates a mosaic of information that helps you understand the duration and rate across sectors at a
deeper level than just going to conferences, or reading press releases of what companies are saying.
Well, it just seems like circling back to your comments earlier about the nineties, where you're right,
anything that had dot-com or dot-net attached to it skyrocketed. Then there was also a second
derivative impact on the real economy. It wasn't just xyz.com that went out of business, but it was the
people that worked there, the supplies they were buying. There's a real economic impact, but you can
reverse engineer that, right?
If you're talking to a staples company or a financials company, it's, "How are you thinking about AI, and
who are vendors that you would work with?" You can maybe use that to circle back to who has a value
proposition that's durable.
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Got it. Brad, regarding the economy, Ameris law posits that as a society, we tend to overestimate a new
technology, pointed out that we did that in the nineties, but then we underestimate it in the out years
or over the longer term.
You're not just a technology investor, you're a generalist. You have to think across your portfolio, and
how this impacts so many. How are you and your partners and the team just maybe thinking about it
from a real economic standpoint, and across your portfolios?
Yeah, it's a great question. At the beginning, we talked about winners, neutral, and losers. I think in
general, for the rest of the economy outside of traditional technology, it's to net neutral to beneficiary.
What it's going to do is drive more efficiency throughout every organization. That could be labor, it
could just be time spent. What I think will happen, and you're already seeing this, is innovation. The
pace of innovation should continue to accelerate.
A couple examples. There's life science companies, pharmaceutical companies that are using AI to help
with drug discovery and molecules. It is just reducing the time to drug discovery. That takes costs out of
Speed to market.
Speed to market.
You're going to see the same thing with content creation, whether that's images, or video, or creative.
Then employees will spend less time doing mundane tasks and spend more time thinking critically and
adding value to services and products that will drive revenue for companies. I think in general, as we
look sector by sector, we think this should be more likely a tailwind than a headwind.
Now, on the flip side, so it's a productivity enhancer, and just in a lot of clients I talked to, I think that's
just a broad assumption that it's a net positive in aggregate for everyone. It probably is when you
average it out, but correct me if I'm wrong. This new technology, it's probably not going to save a
company with terminal value problems already.
A company that was chugging along throughout the 2010s because they were offshoring labor,
benefiting from low interest rates, now these things get exposed with labor costs elevated, capital costs
elevated. Is AI going to protect a struggling company in a recessionary time?
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Maybe in the short term, they can maybe cut costs faster and survive a little longer. If we think
innovation will move forward faster, it would exacerbate the weaknesses of their structural positioning
in an industry. That would be my guess.
The competitiveness will get even...
It should widen.
Right, that makes sense. Bringing it back to, so not just importance of selectivity, those three categories,
category one, two, and three they talk about within tech, but actually on a much broader level, across
the S&P, or across the Russell 1000 growth, across indices broadly.
Yeah, and I don't think we're going to have answers in the next couple of years. This is going to take
three, five, 10 years to see it play out in tangible ways outside of what we're seeing more concentrated
in the technology sector. I think we're still in early innings. All of the news flow and capital flows is really
concentrated in these larger cap technology companies that are just, it is in arms race now to spend and
invest to get this technology up to a certain level of accuracy and reliability, add in the regulatory
Then there's a long tail of companies as they figure out how this helps. In a lot of cases, it may just be
incremental, right? It's turning a conversation into our PowerPoint presentation, so it's not
transformational. It's incremental.
Well, it is amazing, you had that productivity boost in the nineties when we put computers on every
desktop and connected them all through wires, and now it's negative. It went away. Be careful what you
think you know.
Future has no facts.
I think what's exciting, it's been a crazy last couple of years, and I think coming into this year, I think the
thought was we went through COVID, there was winners. Then we got out of COVID, and then there was
a COVID hangover. Companies that sort of participated in this and sort of extrapolated all the trends
that were happening, there's this digestion. There was a thought maybe we're in the later innings of a
lot of these technology shifts that have happened over the last 10 years, whether it was in e-commerce,
or payments, or digital advertising.
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AI. The reason why it happened so fast, literally in the span of six months, and the speed of it and just
the ubiquity of it, everyone can touch and feel this at home on using ChatGPT. It's creating another leg
of growth for the economy and for these companies, which wasn't here, at least apparent, six to 12
months ago. That's different now.
Yeah. Interesting. Brad, thanks so much for joining us.
Yeah, thanks for having me.
While an AI gold rush is underway, it's in early days, and investors have a lot to take on board. Thanks to
Brad for helping us think about the potential risks and rewards of AI in a variety of tech and non-tech
businesses. Thanks to you for listening. For more insights, subscribe to the Strategist's Corner Podcast,
or wherever you get your podcasts.