According to CNBC, BlackRock CEO Larry Fink issued a stark warning in his opening remarks at the World Economic Forum in Davos, Switzerland on January 20. He argued that the artificial intelligence revolution could create even greater wealth inequality, specifically comparing its potential impact on white-collar work to how globalization and outsourcing decreased blue-collar jobs and wages in the late 20th century. Fink urged global business and political leaders to create a “credible plan for broad participation in the gains,” directly referencing plans by CEOs like Amazon’s Andy Jassy and Ford’s Jim Farley to slow hiring and offload work to AI. MIT economist Lawrence D. W. Schmidt agrees the comparison is apt, noting past tech disruptions create “both winners and losers.” Further amplifying the concern, Anthropic CEO Dario Amodei wrote in a personal essay this week that AI could displace half of all entry-level white collar jobs within the next one to five years.
Fink’s Fear Is Rooted In History
Here’s the thing: Fink isn’t just speculating. He’s pointing to a playbook we’ve already seen. The link between globalization and suppressed wages for American workers is well-documented by economic researchers. Companies profited massively from cheaper overseas labor, but the promised “jobs of tomorrow” for displaced factory workers often didn’t materialize at the same pay or in the same communities. Now, swap “overseas factory” for “AI model,” and “blue-collar” for “white-collar,” and you see his point. The cognitive tasks that define many knowledge jobs—data analysis, content generation, basic coding—are precisely what generative AI automates most efficiently. So the risk isn’t just job loss, but a devaluation of expertise and downward pressure on salaries for a huge swath of the workforce.
Winners, Losers, And The AI Dividend
So who wins? In the short term, it’s pretty clear. The immediate beneficiaries are the companies that develop the AI and, more crucially, the corporations that deploy it to cut costs and boost productivity. They get the “AI dividend” of higher profits with a potentially smaller payroll. But Schmidt’s research into how AI impacts the labor market suggests it’s more nuanced. New roles will emerge—AI trainers, ethicists, prompt engineers—but will there be enough of them? And will they pay as well as the jobs they replace? The danger is a bifurcated market: a small elite of highly skilled AI-savvy professionals and managers, and a larger pool of workers whose traditional skills have been commoditized by software. Amodei’s warning about entry-level jobs is especially chilling because it attacks the pipeline. How do you build a career if the first rungs on the ladder are gone?
Beyond Abstractions, A Real Plan?
Fink’s call to move beyond “abstractions” is the real kicker. We’re great at talking about retraining and lifelong learning. But what does a “credible plan” actually look like? It likely has to involve policy levers that are politically tough: rethinking taxation on capital vs. labor, supporting stronger wage growth, and perhaps direct mechanisms like sovereign wealth funds that channel a share of AI-driven corporate profits back to the public. It also means businesses investing in transitioning their workforce, not just replacing it. Basically, it requires treating the social disruption of AI as a core business risk, not just an HR issue. Dario Amodei, in his essay on the technology’s adolescence, frames this as a societal challenge that needs proactive steering. The question is, will companies and governments act before the inequality becomes entrenched? Or will we just repeat the globalization story with a more digital sheen?
