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In this episode, I welcome back Callie Cox, Chief Market Strategist at Ritholtz Wealth Management and author of the excellent Substack, OptimistiCallie. Callie and I dig deep into the tension between Wall Street’s excitement around AI and the more fragile reality of today’s economy.
We cover everything from the sustainability of tech-driven earnings to the risks of over-concentration in the “Magnificent 7.” Along the way, we explore what history can teach us about dominant companies, how to separate hype from durable innovation, and why diversification still matters—even when one sector seems unstoppable.
This conversation blends storytelling and fundamentals, giving you the perspective you need to balance dreams vs. reality as a long-term investor.
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AI Euphoria and a Fragile Economy (02:22)
I kicked off our conversation by asking Callie why investors seem “all in” on AI despite an economy that looks far from perfect. She pointed out that this is a classic reminder that the stock market is not the economy.
Wall Street is pricing in massive expectations for artificial intelligence, and for good reason. AI is a transformative technology with clear potential. We’re already seeing billions poured into data centers, computing equipment, and other infrastructure to support it. That spending is showing up in the numbers, even if it’s still small compared to the overall economy.
But at the same time, the economic backdrop tells a different story. Growth is slowing, inflation remains stubborn—fueled partly by tariffs—and many sectors of the economy are showing cracks. It’s a reminder that the stock market blends reality with expectations, and right now expectations are doing a lot of heavy lifting.
The real question, as Callie frames it, is: how long can those expectations outrun the underlying economy? At what point does slowing growth start to dampen investors’ willingness to dream?
Is Tech Carrying Too Much of the Market? (05:59)
When I think about stock returns, I usually break them into three pieces: earnings growth, cash paid back to shareholders (through dividends or buybacks), and changes in valuation. In good times, investors tend to bid up valuations even if fundamentals look a little shaky. But over the long run, earnings growth is the real engine that drives markets forward.
Right now, those earnings are heavily concentrated in one place: technology. Semiconductors in particular are leading the charge, with Big Tech posting strong profits while many other sectors tread water. Callie pointed out that nearly half of the recent “earnings surprise” in the S&P 500 came from tech alone. The rest of corporate America may be doing better than expected, but it’s hardly blowing growth out of the water.
That’s both impressive and concerning. On one hand, tech has shown remarkable resilience over the past decade, carrying the market through tough periods when other sectors faltered. On the other hand, history tells us that when a single sector drives so much of the growth, the foundation can quickly crack. Weakness in other parts of the economy—whether retailers, industrials, or home improvement giants like Home Depot—eventually weighs on everyone.
As Callie put it, one sector can carry the market for a while, but not forever.
Dreaming vs. Reality in AI Investing (09:37)
One theme that kept surfacing in our conversation is what Callie calls “the ability to dream.” Right now, investors are happy to dream about the possibilities of AI. The story is compelling, companies are spending billions to build infrastructure, and growth hasn’t fallen off a cliff just yet. In that environment, it feels safe to imagine a future where AI drives enormous productivity and profits.
But dreaming only takes you so far. Callie referenced a Jim Chanos quote that says, “It’s easy to dream until reality hits — and then investors put a discount on reality.” That tension is at the heart of today’s market. As long as consumers are spending, the job market holds up, and the economy grows—even slowly—investors will keep dreaming. But if consumer spending falters or layoffs rise, reality will start to erode that optimism quickly.
We’ve seen this before. During the dot-com era, the internet was a world-changing technology. That didn’t stop tech stocks from crashing 80% when the expectations got too far ahead of reality. AI may very well prove transformative over the next decade, but that doesn’t mean the stocks leading the charge won’t face sharp setbacks along the way.
The bottom line? Stories and expectations can fuel markets in the short run, but the fundamentals of the economy always catch up eventually.
Big Tech, GE, and Lessons from History (15:36)
To bring the conversation down from the abstract to something tangible, I shared my own experience with General Electric. GE was once the ultimate blue-chip stock—an innovator that seemed unstoppable. It started with electricity and turbines, then expanded into jet engines, medical technology, television networks, and even banking. For decades, GE looked like the company that could do it all.
But sprawling into too many businesses came at a cost. When the financial crisis hit, GE’s reach exceeded its grasp. Over the last 20 years, while the S&P 500 nearly quintupled, GE lost enormous value and eventually split itself into three separate companies. What was once the face of American innovation ended up as a cautionary tale.
It’s hard not to see parallels with today’s “Magnificent 7.” Apple still leans heavily on the iPhone, Google and Meta rely on ad revenue, and Amazon depends on retail sales. Yet each of them is also stretching into new frontiers—TV, groceries, healthcare, and of course, AI. The risk is that spreading themselves across too many industries could dilute focus and strain profitability, just like GE experienced.
As Callie pointed out, these companies are like corporate Frankensteins: highly profitable, but juggling so many priorities that it’s easy to forget they aren’t invincible. The lesson from history isn’t that innovation is bad. It’s that even dominant companies can stumble when they try to be everything at once. For long-term investors, that’s a reminder to temper excitement about Big Tech’s AI spending with a healthy dose of caution.
Who Really Benefits from AI? (19:29)
When investors talk about AI, the conversation almost always circles back to the same handful of Big Tech names. But as Callie and I discussed, history suggests that the real winners of a new technology aren’t always the giants pouring billions into research and development. Sometimes it’s the companies applying the technology—quietly improving productivity and profitability—who capture the upside.
Think about it this way: Amazon, Google, and Microsoft may build the infrastructure, but the companies using that infrastructure to streamline their businesses could be the ones who actually reap the rewards. In fact, many of the 485 companies in the S&P 500 outside of the Mag 7 are just starting to explore how AI can help them cut costs, optimize workflows, and boost profits.
Callie shared some great examples of where investors might look beyond the obvious names. Data centers, for instance, are essential to AI’s growth, but the pure-play opportunities often come through real estate investment trusts (REITs), which trade more like real estate than tech. Semiconductor suppliers, infrastructure companies, and even “old economy” businesses adopting AI in practical ways could benefit just as much—if not more—than the headline-grabbing giants.
The key point: AI is bigger than Big Tech. The ecosystem stretches across industries, and history tells us that nimble, smaller players often capitalize on innovation more effectively than sprawling incumbents. For investors, that’s a reason to think beyond the usual suspects and keep diversification front and center.
Concentration Risk and Portfolio Volatility (21:53)
One of the biggest risks in today’s market is how much investor portfolios hinge on just a handful of companies. Roughly a third of the S&P 500’s value is concentrated in the so-called “Magnificent 7,” and much of that strength is tied to the AI narrative. That means when headlines hit—good or bad—they can move the entire market in dramatic ways.
Callie highlighted how fragile this setup can feel for everyday investors. For example, when news broke about a Chinese AI company with supposedly more efficient technology, Nvidia shares tumbled and the shock rippled across portfolios. The story ultimately faded, but it underscored just how vulnerable the market is to surprise headlines when so much weight rests on a few stocks.
For long-term investors, concentration risk isn’t just an academic concept—it’s an emotional one. Even if you believe in the future of AI, watching your portfolio swing by 2–3% in a single day can make it harder to stick to your plan. Those stressful days often test discipline more than down markets themselves.
The lesson here is clear: concentration magnifies volatility. While the Mag 7 may be powering market returns today, they also bundle significant risk into your portfolio. Diversification and a well-thought-out plan aren’t just about smoothing returns on paper—they’re about protecting yourself from the emotional whiplash that can lead to costly mistakes.
Balancing Story vs. Evidence as a Long-Term Investor (24:51)
Markets are built on a blend of hard data and human imagination. Valuations aren’t driven only by current earnings and dividends—they also reflect how confident investors feel about the future. That’s why stories can be so powerful. A compelling narrative, like the rise of AI, gives investors permission to “dream” and bid up prices even when the fundamentals aren’t fully there yet.
But as Callie and I discussed, that doesn’t mean long-term investors should dismiss stories altogether. Stories are how humans process uncertainty. They help us frame risk and opportunity. In fact, a little bit of dreaming can be healthy if it keeps investors engaged and willing to take on the risk that comes with owning stocks. The danger is when you let stories replace evidence.
In practice, this means recognizing that short-term valuations may swing on narratives, but long-term returns are driven by reality: earnings growth, productivity, and the health of the economy. For most investors, the goal isn’t to eliminate stories—it’s to keep them in perspective. If you’ve reached a certain level of wealth, you may even decide to carve out a small part of your portfolio to invest in “story stocks,” knowing they carry more risk. But for your core holdings—the money that will fund your retirement and your future—you want to anchor in evidence, not just expectations.
At the end of the day, stories can make investing exciting, but reality is what drives portfolios forward. Long-term investors need both: the discipline to stay grounded in fundamentals and the humility to understand that expectations will always play a role in market prices.
What Could Prove AI’s Impact Is Real? (29:15)
Hype and hope can move markets for a long time, but eventually new technologies have to prove their worth in the data. So I asked Callie what signs she’s watching that would confirm AI’s impact is more than just a good story.
She pointed to a few encouraging developments already underway. Business surveys show adoption rates climbing quarter after quarter, with more companies experimenting with AI in daily operations. Corporate spending on AI-related infrastructure—everything from data centers to specialized equipment—has surged, showing up in GDP data at a pace few expected. On earnings calls, we’re starting to hear examples from firms like Dell and Accenture describing how AI is streamlining their workforces and improving efficiency.
But Callie emphasized that the ultimate proof will come from productivity gains. Over the long run, durable technologies boost output per worker, and that’s what drives sustainable growth. If AI really is as transformative as promised, it should eventually show up in productivity statistics—though history reminds us that adoption curves take years, not quarters.
In the meantime, she also flagged more qualitative milestones, like whether AI can handle everyday tasks in ways that feel seamless. Something as simple as reliably managing an email inbox could be a breakthrough sign of real-world value. Until then, we’re in the messy middle: plenty of promise, early signs of impact, but not enough evidence to declare victory just yet.
Resources:
- Check out Callie’s Substack, OptimistiCallie
- Follow Callie on Twitter/X and LinkedIn
- EP 95: What Is Direct Indexing?
- EP 99: The Problem With Investing In Bond Indexes
- Check out my first conversation with Callie Cox, EP 136: Decoding 2024’s Investment Landscape
The Long Term Investor audio is edited by the team at The Podcast Consultant
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