Artificial intelligence (AI) dominates conversations about efficiency and output, but is it driving the current productivity surge? While AI holds immense potential, macroeconomic data suggests that today’s gains mostly stem from more traditional forces. Understanding the nuanced relationship between AI and productivity requires a deeper look into the interplay of capital investments, labor trends, and technological advancements.
The Real Drivers Behind Recent Productivity Gains
During the COVID-19 pandemic, businesses invested heavily in modernizing aging infrastructure, upgrading technology, and strengthening supply chains to support remote work and manage disruptions. Those upgrades are now delivering measurable productivity improvements, and this trend notably began before the launch of ChatGPT.
While AI is undoubtedly a growing focus in boardrooms, its measurable impact on macroeconomic productivity is likely years away. For now, improved infrastructure and operational efficiencies remain the primary contributors to growth.
Labor Market Shifts and the Productivity Upcycle
The U.S. is entering a long-term productivity upcycle driven by structural changes in the labor market following decades of low-cost, abundant labor, which reduced companies’ urgency to innovate. Now, demographic shifts, including Baby Boomer retirements, lower birth rates, and reduced immigration, are tightening the labor market, pushing wages higher and threatening to squeeze corporate margins.
To remain profitable, businesses are increasingly turning to automation and technology. AI is expected to enhance this shift over time, but it is not yet the dominant force behind current performance.
Is There an AI Bubble?
As capital floods into AI, concerns about an investment bubble are natural. Today’s environment, however, appears healthier than past speculative periods: most funding is equity-based, leaving corporate balance sheets strong and potentially limiting systemic risk.
That said, recently rising debt issuance in the technology sector warrants monitoring. Companies betting heavily on AI need to demonstrate clear paths to profitability to justify valuations. Investors should remain cautious as financial conditions evolve, avoiding overexposure to speculative plays.
Strategic Takeaways for Investors
As the AI hype cools, investors must shift from chasing speculative opportunities to focusing on quality assets. Companies with proven business models, strong cash flows, and clear automation strategies stand to benefit most from the productivity upcycle.
The productivity boom is real, but its drivers are so far still more grounded than headlines suggest. Understanding the dynamics of labor market shifts, capital investment, and AI integration is essential for capturing long-term value while mitigating risks.
For more information on these and other investment, political, and economic trends, please listen to our podcast, Monthly Macro: Geopolitics, Inflation, and the Fed, featuring William Blair macro analyst Richard de Chazal.