Latest / Stagflation Conversations with Fexingo: High Inflation, Slow Growth, and 1970s Echoes / How AI Is Fueling Stagflationary Productivity Paradoxes
Transcript
- Lucas: Look at the numbers coming out of July for the Consumer Price Index. Core CPI, which strips out food and energy, sat at 336.8. It ticked up slightly from 336.06, but the real story is what it’s doing relative to real GDP growth, which has slowed to just one point five percent annualized. We are seeing prices stick while the engine of economic expansion sputters. Luna: Right, and that feels less like a classic demand-pull inflation and more like a supply-side squeeze where we can’t quite get the efficiency gains we promised ourselves would arrive by now. Lucas: Exactly. And this brings us to the elephant in the room: artificial intelligence. Everyone assumed generative AI would be the ultimate deflationary shock, driving down labor costs and skyrocketing productivity. But if you look at the broader economy, we aren't seeing that wage suppression or mass output surge yet. Instead, we see a divergence where tech giants report massive margins while the rest of the economy feels the pinch of thirty-three dollar an hour average hourly earnings barely keeping pace with services inflation. Luna: It feels like we’re paying for the transition rather than benefiting from the destination. The capital expenditure on chips and data centers is huge, but does that actually lower the price of a haircut or a healthcare visit? Lucas: No, it doesn't. In fact, it might be making things worse in the short term. When companies spend billions on infrastructure that doesn't immediately translate to consumer price reductions, you get a weird stagflationary dynamic. You have high costs embedded in the system—energy for those data centers, salaries for specialized engineers—but no corresponding drop in the goods and services people buy. It’s a cost-push scenario disguised as a technological breakthrough. Luna: So the promise of AI efficiency is getting trapped inside corporate balance sheets rather than flowing through to consumers. Lucas: Precisely. And this creates a problem for policymakers. If the Federal Reserve sees inflation sticking because these new technology costs are structural, they might keep rates higher for longer. But higher rates hurt the very sectors trying to invest in that future. It’s a catch- twenty-two where the cure for inflation might suffocate the growth needed to make the technology pay off. Luna: And let's not forget the job market. JOLTS data shows job openings are still relatively high at seven thousand two hundred seventy-one thousand, even as nonfarm payrolls dipped slightly. Employers are hoarding talent because they don't know how much AI will actually replace versus augment roles yet. Lucas: That hoarding behavior keeps wages elevated. If workers aren't being replaced by AI today, they're demanding premiums for the uncertainty of tomorrow. So you have wage growth supporting consumption, which supports prices, preventing the disinflationary spiral analysts predicted. Luna: It’s fascinating how the narrative shifted so fast from 'AI will cause mass unemployment' to 'we need more AI talent.' The labor market is resisting the deflationary pressure. Lucas: I think there’s also a psychological component here. Consumers expect AI to make things cheaper, so when it doesn't, frustration mounts. But businesses are passing on the costs of this digital transformation. They’re treating AI integration like a tax on modernity that customers just have to absorb. Luna: Which brings me to our community support. If walking through the economy with us has made something click, especially regarding these complex shifts in how technology intersects with your wallet, consider supporting the show. It helps us keep digging into the data without ads interrupting the flow. You can find us at buy me a coffee dot com slash fexingo. Lucas: We really appreciate it. It allows us to spend more time on deep dives like this rather than chasing clicks. Now, back to the data. Luna: Yeah, thanks for that. Let's talk about the sectoral differences. Are we seeing this everywhere, or is it concentrated in specific industries? Lucas: It’s highly concentrated. Services inflation remains stubborn because those jobs are hard to automate quickly. A nurse, a teacher, a plumber—they all need human presence. Meanwhile, software and digital goods are seeing price stability or even declines. But since housing, healthcare, and insurance make up such a large chunk of the CPI basket, the digital deflation isn't pulling the average down enough. Luna: So the basket composition matters more than the headline tech hype. We’re feeling the pain in the areas AI hasn't cracked yet. Lucas: Correct. And consider the energy angle. Those data centers require massive amounts of electricity. With global power grids already strained, the demand from AI could push up energy prices, which then feeds back into logistics and manufacturing costs. It’s a secondary inflationary channel that most people overlook. Luna: That’s a great point. The physical footprint of the digital economy is heavier than we realized. It’s not just code; it’s copper, concrete, and cooling systems. Lucas: Exactly. And this ties back to the bond market. Ten-year breakeven inflation is sitting at 2.31 percent, flat recently. Investors are skeptical that the Fed can tame these structural costs without causing a recession. They’re pricing in a slow grind of inflation rather than a sharp correction. Luna: Which makes the equity markets look particularly fragile. If growth is slowing to one point five percent, valuations based on perpetual double-digit tech growth start to look expensive. Lucas: The S&P 500 is at 7,631, but the Russell 2000 is down nearly three percent over the last five days. Small caps are getting crushed because they can’t absorb the AI investment costs like the mega-caps can. This is a bifurcation happening in real-time. Luna: So the market is rewarding incumbents who can scale AI, while punishing everyone else who is just trying to survive the cost environment. Lucas: Yes, and that’s dangerous for economic health. Innovation usually comes from agile startups, not entrenched giants. If the playing field tilts too far, we risk long-term stagnation masked by short-term profit margins. Luna: It feels like we’re in a holding pattern. Waiting for the AI revolution to mature enough to deliver the promised efficiency, while dealing with the immediate inflationary side effects. Lucas: And waiting for the Fed to figure out whether to fight the current inflation or prepare for the next downturn. Their hands are tied by this ambiguous data set. Luna: With unemployment still low at four point one percent, they can’t cut rates aggressively. But raising them further might break the small-cap segment entirely. Lucas: Right. So they likely stay on hold, hoping that the productivity genie eventually gets out of the bottle. But until it does, we’re stuck with this messy middle ground. Luna: It’s a reminder that technology doesn’t operate in a vacuum. It interacts with monetary policy, labor dynamics, and global supply chains. Lucas: Absolutely. The narrative is never just about the tech itself. It’s about how the tech reshapes the underlying economics of production and consumption. Luna: Do you think we’ll see a tipping point where AI finally drags down services inflation, or is the human element too resistant to change? Lucas: I think we’ll see incremental changes. Customer service chatbots, automated legal document review, personalized tutoring. These will lower costs in specific niches, but the broad-based impact will be gradual. It won’t be the sudden deflationary cliff some predicted. Luna: So patience becomes the key strategy for investors. Holding through the volatility while the ecosystem matures. Lucas: Or perhaps hedging against the inflation that persists in the meantime. Diversification across assets that benefit from both growth and price increases seems wise right now. Luna: Gold and commodities might still have a role, given the currency debasement fears and the energy demands of AI. Lucas: Spot gold dropped five percent recently, which is interesting. Maybe the market is betting on a soft landing after all. But I’d be cautious. The structural pressures haven’t vanished. Luna: Agreed. Caution is the name of the game. We’re navigating uncharted territory where old models don’t quite fit the new reality. Lucas: Well said. It’s a complex landscape, but understanding these nuances gives us a better map than just following the headlines. Luna: Thanks for tuning in. Stay curious, and keep questioning the narratives.