The Productivity Boom Is Arriving. Why Investors Should Care.

As I argued here just over a year ago, the most important economic impact of artificial intelligence was unlikely to come from sudden job displacement, but from incremental, economy‑wide efficiency gains that raise output per worker over time. New data suggest this dynamic is beginning to show up in the aggregate numbers. What once looked like a theoretical possibility increasingly resembles an early-stage productivity boom — one with meaningful implications for investors.

For much of the 2010s, U.S. productivity was conspicuously weak despite rapid technological progress. That disconnect fueled concerns about secular stagnation and declining growth potential. Today, those concerns look overstated. Productivity growth has strengthened meaningfully. 

A Resilient Economy, Without a Recession

In recent years, the U.S. economy has proven much more resilient than most expected.

Economic commentary over the past few years has highlighted the expectation of either a “soft landing” or an outright economic recession. Yet the data have pointed in a different direction. Real GDP growth has remained solid, with output expanding at a pace more consistent with a healthy expansion than with an economy on the brink of contraction.

During the fourth quarter of 2025, real growth is estimated to have expanded at a solid pace of 4.2%, driven in part by strong domestic private sector investment growth. One challenge, however, is that this strength is emerging without the robust labor force growth that typically accompanies a strong expansion. The result is productivity‑intensive growth.

What makes this episode distinctive is not just the level of growth, but its composition. Unlike past periods of strong GDP growth, the current expansion is not being accompanied by strong job growth. This is due, in part, to labor force growth that has been historically slow — reflecting demographics, lower immigration flows than in prior cycles and the natural limits of post‑pandemic labor reentry.

The result is that economic output is rising faster than labor input, meaning productivity increases.

Capital Investment Is Doing the Heavy Lifting, and AI Is Central to the Story

As we all know by now, investment in AI has been robust. Tech firms have continued to invest more heavily in software and research and development (R&D) than most people anticipated, rising by roughly $180 billion versus a year ago.

In addition to contributing to economic growth, AI investment has been key in translating labor constraints into higher productivity. Consider the recent boost from technology companies pursuing the promise of AI’s potential. The investments have been productivity boons for tech companies that can scale rapidly.

Unlike earlier waves of IT investment (like the 1990s internet revolution) that mainly improved information flow, today’s AI systems directly augment cognitive and operational tasks. They write first drafts, summarize documents, generate code, optimize logistics routes, screen resumes and support customer interactions. In economic terms, AI functions as a form of scalable labor: it allows a given worker to supervise, validate and deploy far more output than before.

As I have previously argued, should the recent gains in productivity prove sustainable, this will matter a lot for companies and the overall economy.

Higher productivity increases corporate profit margins by increasing output and containing labor costs. It also helps support consumption growth and might even help to slow the burden of rising federal debt relative to GDP, another pressing issue, and one that politicians far too often brush aside.

In the near term, AI’s impact shows up first where labor is scarce or the scope of work is more narrow or constrained. While the implications of when, if ever, AI reaches artificial general intelligence (AGI) is a fascinating topic to consider, crucially, AI gains do not require explosive growth in IT spending or perfect models.

Even imperfect tools generate productivity benefits when deployed at scale and embedded into workflows. That is why productivity can rise even as headlines debate whether AI investment is overhyped or overly capital-intensive. So far, the data reflect rapid adoption, not hype.

Why This Is Not a Labor Shock — At Least Yet

Importantly, rising productivity has not yet come with widespread labor market stress. Layoffs remain relatively contained, unemployment claims are moderate, and firms appear to be absorbing technological capacity without aggressively shrinking payrolls. At this stage, machines are supplementing labor rather than replacing it outright. This dynamic reinforces the argument from my prior article that AI’s economic importance lies less in sudden job replacement and more in pervasive, incremental efficiency gains across the economy.

Things could change, of course, but so far, the productivity transition has unfolded relatively smoothly. Workers have shifted toward oversight, coordination, and judgment‑intensive roles, while software and machines handle routine or repetitive tasks. This has allowed productivity to rise while employment remains broadly stable.

For the macroeconomy, should this scenario continue, the result is constructive. Productivity‑driven growth eases inflationary pressure by restraining unit labor costs, allowing real incomes to rise without forcing the Federal Reserve to engineer a slowdown through higher short-term interest rates.

What This Means for your Portfolio: Implications for Inflation, Profits and Valuations

The implications alluded to above are particularly important for the macroeconomy. When productivity growth outpaces wage growth, unit labor costs tend to moderate. This is the most benign form of disinflation: prices stabilize not because demand collapses, but because supply becomes more efficient.

For firms, that same mechanism supports profit margin expansion. Higher output per worker improves operating leverage, especially outside the most labor‑intensive industries. Unlike margin gains driven by temporary pricing power, productivity‑based margins are more durable and broadly distributed across sectors.

This strengthens the earnings outlook and provides a more solid foundation for equity valuations than a narrow, capital‑intensive tech boom alone. This means that gains in the stock market could broaden beyond the narrow Magnificent Seven megacap tech stocks. In effect, AI-driven productivity gains should increasingly begin to benefit the firms that use the technology, not just those that create it.

What this Means for New College Graduates in an AI-Driven Economy

The same AI-driven productivity gains reshaping aggregate growth also help explain why recent college graduates face a more challenging entry-level job market, even in a strong economy. When firms can expand output through technology rather than headcount, hiring becomes more selective. Entry-level roles that once served as training grounds are increasingly compressed, redesigned, or absorbed into more senior positions supported by AI tools.

This is not because demand is weak. It is because AI changes the economics of early-career work. Tasks traditionally assigned to junior employees — drafting, data cleaning, basic analysis, routine research — are precisely the areas where AI is most effective. As a result, firms need fewer workers performing purely preparatory tasks and more workers who can exercise judgment, integrate information and oversee automated outputs.

For new graduates, this raises the skill threshold for initial employment. The premium shifts toward candidates who can demonstrate fluency with AI tools, strong analytical reasoning, and domain-specific understanding. In effect, AI accelerates the transition from “learning by doing” to “learning by supervising.” Graduates who can quickly add value alongside technology are better positioned than those expecting traditional apprenticeship-style roles.

Over time, a productivity-led expansion should support higher real wages and more sustainable career paths. But the transition can feel counterintuitive: strong GDP growth alongside a tougher entry-level market. Understanding that tension is critical. It reflects not economic weakness, but an economy learning how to grow faster with fewer traditional workers — by embedding AI directly into production.

A Different Kind of Expansion

Step back, and the picture becomes clearer. This does not look like a late-cycle bounce or a narrowly avoided recession. It looks like the early stages of an AI-driven growth regime. The economy is expanding at a solid pace. The labor force is not. Productivity is filling the gap.

AI sits at the center of that shift. Not as science fiction, and not as a hiring apocalypse — but for now as a set of tools that let firms get more out of the workers they already have. That is how output keeps rising even as headcount growth slows. It is also why inflation pressures are easing without a collapse in demand.

Economist Ed Yardeni has described this decade as the Roaring 2020s. That once sounded optimistic. It now sounds increasingly plausible. Real GDP is growing. Productivity is on the rise. Inflation is cooling. Those are not the hallmarks of a tired cycle. They are the ingredients of a structural upgrade.

If history is any guide, big economic stories often feel underwhelming while they are happening. They show up quietly in the data before they dominate the narrative. The productivity gains now emerging suggest that AI has crossed that threshold — from promise to production. If so, the defining feature of this expansion will not be how gently the economy landed, but how much higher technology helped it climb.