BlackRock CEO Larry Fink warned at the World Economic Forum in Davos on January 20, 2026, that artificial intelligence risks repeating globalization’s damage to blue-collar jobs, this time targeting white-collar roles and widening wealth gaps. “If AI does to white-collar work what globalization did to blue-collar work, we need to confront that directly. Not with abstractions about ‘the jobs of tomorrow,’ but with a credible plan for broad participation in the gains,” Fink said, as reported by CNBC.
MIT associate professor of finance Lawrence D. W. Schmidt, who studies AI’s labor market effects, sees parallels to past disruptions like the digital age and logistics revolutions, which devalued expertise while opening new doors. Generative AI now eyes repetitive cognitive tasks in office jobs, with Amazon’s Andy Jassy and Ford’s Jim Farley citing it for headcount cuts or hiring freezes. Anthropic CEO Dario Amodei predicts in an essay that AI could displace half of entry-level white-collar positions within one to five years.
Yet a Yale University Budget Lab study from October found no broad labor market upheaval since ChatGPT’s 2022 debut. Nvidia’s Jensen Huang countered fears at the 2025 Milken Institute Global Conference: “You’re not going to lose your job to an AI, but you’re going to lose your job to someone who uses AI.”
AI’s Hidden Productivity Promise
Schmidt argues effective AI deployment boosts company revenue and headcount, creating a “rising tide that lifts all boats-type of phenomenon.” Companies embracing AI grow, generating “enormous opportunity for swaths of new work that weren’t there before.” Workers must pivot: use AI to amplify productivity, then shift time to human strengths like communication, creativity, and critical thinking—areas where AI falters.
“Find ways for AI to make you more productive, and reallocate the rest of your time ‘towards things that AI is not good at,’” Schmidt advises in the CNBC interview. Employers should offer job security guarantees to staff cooperating on AI integration, fostering efficiency without fear.
“The more that we can devote our energy towards capturing [AI’s] benefits—making sure that those who would be displaced by AI are instead those who learn to work with AI and do their job in a different way—the better the future of work looks,” he adds.
Lessons from MIT’s Broader Research
MIT’s research echoes Schmidt’s call for augmentation over replacement. A March 2025 MIT Sloan study introduces the “EPOCH” framework—evaluating human capabilities like empathy, problem-solving, originality, collaboration, and hands-on skills—showing AI complements these, with human-intensive tasks rising from 2016 to 2024. “The research points to the need to invest in the development of workers’ EPOCH capabilities to gain the benefits from helping workers become complementary to—and not replaced by—AI,” per MIT Sloan.
Nobel laureate Daron Acemoglu, in a May 2025 MIT Sloan video, urges partnering with skilled employees to pinpoint AI uses: “Use AI to augment human workers, not replace them.” His work predicts AI automates just 5% of tasks, adding 1% to global GDP this decade, far below hype, as detailed in MIT Sloan Management Review.
Acemoglu’s “Simple Macroeconomics of AI” paper estimates U.S. productivity gains at 0.7% over 10 years, emphasizing redirection toward worker tools. “We’re using it too much for automation and not enough for providing expertise and information to workers,” he states in MIT Economics.
Real-World Augmentation Wins
David Autor, another MIT labor economist, envisions AI rebuilding the middle class by enabling less-educated workers to tackle complex tasks. A software firm pilot showed ChatGPT-assisted customer service reps boosting output 14% on average, with novices reaching veteran proficiency in three months versus ten, aligning with Schmidt’s vision from a 2023 NPR transcript updated in recent discourse.
MIT Sloan’s December 2025 analysis stresses new jobs from productivity, not cost cuts: economists like Acemoglu and Erik Brynjolfsson agree true boosts come from augmenting nurses, teachers, and factory workers, per MIT Technology Review. A Fortune report notes IMF chief Kristalina Georgieva seeing AI spillovers benefiting low-wage workers via productivity.
On X, economist Alex Imas highlighted task bundles: automating some raises value of irreplaceable human elements, potentially lifting wages, citing research by Joshua Gans and Avi Goldfarb. DeepMind’s Séb Krier argues full substitution demands fragile assumptions, predicting prolonged “cyborgism.”
Policy Paths to Shared Gains
Acemoglu and Simon Johnson advocate “pro-worker AI” policies: counter automation bias with worker voice, training, and incentives for augmentation. Their memo warns displacement cascades wages downward, even for high earners, urging platforms for collaboration over surveillance, as in MIT Sloan.
Employers guarantee jobs for AI collaborators; governments fund reskilling. Schmidt reinforces: firms pledging security spur cooperation. Recent X discussions, like Kevin Bryan’s endorsement of complementary task models, show rising tide potential if workers adapt first.
Global South risks loom, with AI surveillance exports noted by Acemoglu in MIT News. Yet optimism persists: MIT’s Shaping the Future of Work Initiative, led by Acemoglu, Autor, and Johnson, targets equitable trajectories through pro-worker tech steering.
Frontlines of Adaptation
Hands-on fields like electricians and plumbers stand to gain most from reliable AI diagnostics, Acemoglu notes in MIT Sloan, though hallucinations hinder now. Craftspeople using AI for troubleshooting could see outsized boosts, leveling expertise.
X user Josh Schultz predicts labor’s revenue share dropping as AI rises to 8-12%, urging early adoption. Jackson warns of management thinning but opportunity for agile youth stacking skills.
Schmidt’s core message endures: AI as ally demands proactive embrace. By reallocating to uniquely human domains and demanding inclusive policies, workers seize control of tech’s trajectory, ensuring growth broadens prosperity.