Market Outlook

May 1, 2026

AI Investors Take A Page From History


John Bonnanzio From time to time, markets have been rattled this year and last by the technology sector’s gargantuan capital investments in AI generally, and of billion-dollar data centers in particular. To offset some of these capital expenditures (capex), Meta and Microsoft are among the latest to have announced significant headcount reduction schemes (layoffs and early retirements). Most such moves have been embraced by investors with upticks to their share prices.

Granted, improving balance sheets in the short term typically dampen concerns among Wall Street’s traders. But in a brain-powered arena such as tech/AI, some worry that the loss of intellectual capital in the form of employees may fester into longer-term shortcomings. Indeed, with the law of unintended consequences still immutable, history provides endless examples of both government policies and short-term thinking that have had disastrous consequences.

Big Four Capex (in $billions)

On the policy/government side, prohibition did nothing to curb drinking, but it certainly fueled organized crime. And, at the start of the Great Depression, the Fed tightened the money supply to curb market speculation, but that led to severe deflation and bankruptcies. And unlike its actions during the Financial Crisis and Covid shutdowns, it failed to act as a lender of last resort which wiped out banks and Americans’ savings.

More "recently," price controls in the early 1970s fanned inflation, and when applied to crude oil, exacerbated shortages.

Most profoundly, the 2001 admittance of China into the World Trade Organization without a prerequisite level playing field (in terms of democratic values, worker parity and environmental controls), did help to lower prices in the U.S. However, with Chinese imports quadrupling in just 10 years, it accelerated the decline in U.S. manufacturing (excluding software, etc.) and facilitated long-term unemployment, especially in cities. As for U.S. business strategies that have backfired, in the 1950s and ’60s the steel industry didn’t take seriously newer and more efficient technologies developing in post-war Germany and Japan. Refitting old open hearth mills instead of investing in continuous casting and, later, electric mini mills, eventually led to the industry’s collapse. Early "tech" companies also self-destructed. RCA and Zenith once dominated the TV market. But with their reliance on vacuum tubes coupled with their reticence to invest in cheaper and more reliable semiconductors, they handed their market to Sony and other Japanese companies.

Other examples of entire industries disappearing, at least in part, owing to their focus on quarterly profits rather than future growth include textiles, furniture and perhaps most importantly, automobiles, where 400,000 jobs were lost (30%) in a five-year period ending in 1982.

Fast-forward to this century and there’s Boeing’s near-exclusive focus on shareholder returns, while investing little in quality control, safety and innovation. Against the backdrop of two MAX 737 crashes, in 2024, Airbus surpassed Boeing in commercial aircraft sales.

Inevitable Missteps
While AI will inevitably create numerous problems with unforeseen consequences, there are less-discussed consequences to companies that fail to incorporate AI into their business practices. As history shows, when productivity lags behind competitors, it’s at first hard to detect, then it’s suddenly catastrophic. That’s true for a single company and it’s also true for an entire country. So while it’s possible that an AI "glut" is building and that some players will pay a price, history shows that it’s better to err on the side of investing too much, rather than too little.

— John Bonnanzio