A Point of No Return for Corporate AI Strategy
American companies may be approaching what one leading economist calls an AI Cortés moment, a decisive turning point in artificial intelligence adoption that could fundamentally reshape hiring patterns and productivity across the economy.
Mark Zandi, chief economist at Moody’s Analytics, argues that businesses are increasingly committing to AI in ways that make reversing course difficult. The term references Spanish conquistador Hernán Cortés, who famously burned his ships after arriving in Mexico in 1519, eliminating any possibility of retreat.
For corporate America, Zandi believes the analogy reflects how firms are investing heavily in AI systems, restructuring operations, and making strategic bets that lock them into an AI-driven future.
Workforce Cuts Raise Questions About AI’s Role
The discussion gained traction after fintech company Block announced plans to cut roughly 40 percent of its workforce. While the company did not explicitly attribute the move to artificial intelligence, Zandi suggested the connection was difficult to ignore.
Writing on LinkedIn, he said the decision signaled how companies might be quietly aligning themselves with AI-driven efficiency strategies.
Even if artificial intelligence is not the sole cause of workforce reductions, Zandi argues that market reactions could accelerate the trend. Block’s share price rose following the announcement, a signal that investors may reward companies that pursue aggressive cost-cutting and automation strategies.
That market feedback loop could push other companies to adopt similar restructuring plans. If executives believe AI-driven efficiencies will be rewarded by investors, widespread imitation could follow.
Hiring Weakness May Signal Early AI Impact
Despite growing concern about automation, the U.S. labor market has not yet experienced widespread AI-driven layoffs. Instead, Zandi says the effects may be appearing in a less visible way, through slower hiring.
Speaking during a recent virtual discussion on artificial intelligence and the economy alongside economists from Goldman Sachs and Yale University, he pointed to a notable disconnect between hiring trends and expectations for productivity.
Technology job openings have declined, overall hiring rates remain subdued, and layoffs recently reached their highest level since 2009. However, Zandi stresses that the emerging pattern is less about job cuts and more about fewer new positions being created.
Surveys also reveal an apparent contradiction. According to the National Bureau of Economic Research, more than 80 percent of companies report no measurable impact from AI on employment or productivity over the past three years. At the same time, those same firms expect AI to boost productivity by roughly 1.4 percent over the next three years.
That divergence, declining hiring alongside anticipated productivity gains, is what Zandi views as a defining sign of the AI Cortés moment.
When Productivity Arrives, Companies May Move Quickly
If AI-driven productivity gains begin to materialize, companies may implement them at scale rather than gradually.
In practical terms, that could mean consolidating roles, automating workflows, and deploying AI agents across departments that once required large teams. The shift would not necessarily come as a sudden shock, but rather as a series of rational corporate decisions that collectively reshape the labor market.
Zandi’s broader concern centers on how quickly these changes could cascade once early adopters demonstrate financial success.
Massive Investment Signals Long-Term Commitment
The scale of financial investment behind artificial intelligence also suggests companies are preparing for long-term transformation.
According to Moody’s analysis, the ten largest AI-focused companies are expected to issue more than $120 billion in bonds, potentially setting a record for debt financing in the sector. Analysts have drawn comparisons to the capital spending wave during the late-1990s technology boom.
The difference, however, lies in how the expansion is being financed. While the dot-com era relied heavily on equity markets, much of today’s AI buildout is supported by corporate debt. That structure could amplify the consequences if expectations around AI fail to materialize.
Four Possible Paths for the AI Economy
In recent research, Zandi outlined four potential scenarios for how the AI economy could evolve through 2026.
The most likely outcome, with an estimated 40 percent probability, is a steady productivity-driven expansion powered by AI adoption. Another scenario, assigned a 20 percent probability, envisions significant labor market disruption if automation spreads faster than workers can adapt.
A third possibility, which Zandi assigns a 25 percent chance, involves a correction if AI investments fail to deliver expected returns. The final scenario, with a 15 percent probability, mirrors the productivity surge seen during the 1990s technology boom.
For now, one sector continues to support employment growth: healthcare. Zandi has noted that without the industry’s steady job creation, the broader economy could already be experiencing net job losses.
The larger question is whether businesses, once fully committed to artificial intelligence, will have the flexibility to slow the transition if labor market disruptions accelerate. If Zandi’s analogy holds, many companies may soon find themselves in a position similar to Cortés’ expedition, moving forward because turning back is no longer an option.
