Sal Khan, founder of Khan Academy, warns that artificial intelligence will displace workers at an unprecedented scale and argues companies must invest their AI-driven profits into workforce retraining programs.
Khan has spent over a decade democratizing education through free online learning. His organization now incorporates AI tutoring tools, giving him direct insight into how the technology is reshaping skill development and learning. Speaking with The New York Times, Khan outlined both the transformative potential and disruptive risks AI poses to employment across industries.
Workforce Transformation Accelerates
The displacement Khan describes differs from previous technological disruptions in speed and scope. While automation has historically affected specific sectors like manufacturing, AI threatens to reshape knowledge work, creative industries, and service jobs simultaneously. Tasks ranging from customer service to legal research to graphic design face automation within years rather than decades.
Khan points to AI’s ability to perform cognitive tasks previously requiring human judgment. Language models can write, analyze data, generate code, and solve complex problems. As these capabilities improve and costs decrease, economic pressure will push companies toward AI solutions even in sectors traditionally insulated from automation.
The timeline matters significantly. Past industrial transitions occurred over generations, allowing gradual workforce adaptation through normal retirement and new worker training. AI’s rapid advancement compresses this adjustment period, potentially creating severe dislocation for workers in mid-career with specialized skills that become obsolete.
Corporate Responsibility for Retraining
Khan advocates for a direct link between AI profits and worker retraining. Companies deploying AI to reduce labor costs should allocate portions of resulting savings toward reskilling programs. This approach treats workforce adaptation as a business responsibility rather than leaving it entirely to government or individual workers.
The proposal recognizes that companies benefit most directly from AI deployment and possess specific knowledge about which skills will remain valuable. A tech firm automating customer service understands what roles will grow in its operations and can design targeted training accordingly.
Some corporations have initiated retraining programs, though scale remains limited. Amazon, for instance, has pledged billions for upskilling initiatives. However, these efforts often focus on existing employees rather than workers displaced from other companies or industries.
Education Systems Face Pressure
Khan Academy itself exemplifies education’s AI transformation. The platform now offers AI-powered tutoring that adapts to individual learning styles and provides personalized feedback. This demonstrates both opportunity and challenge: AI can make quality education more accessible while potentially reducing demand for human educators.
Traditional education systems struggle to keep pace with rapidly changing skill requirements. College degrees take years to complete, by which time industry needs may have shifted. Khan suggests education must become more modular and continuous, with workers regularly updating skills throughout careers rather than front-loading learning in early adulthood.
The educational technology sector is exploring micro-credentials, competency-based learning, and just-in-time training models. These approaches could help workers pivot more quickly than traditional degree programs allow.
Policy and Economic Implications
Khan’s argument raises questions about economic structures surrounding AI deployment. If companies capture productivity gains while workers bear adjustment costs, wealth concentration accelerates and social stability suffers. Linking corporate AI profits to retraining costs attempts to internalize these externalities.
Critics might argue this places unfair burdens on innovative companies or that competitive pressures make voluntary contributions unrealistic. They could suggest government intervention through taxation or regulation provides more reliable funding for workforce programs.
Others question whether retraining alone suffices if AI eliminates more jobs than it creates in accessible fields. This scenario might require broader policy responses like work-sharing arrangements, universal basic income, or redefined measures of economic contribution beyond traditional employment.
Preparing for Disruption
Khan emphasizes urgency in addressing workforce displacement before it reaches crisis levels. Waiting until millions lose jobs simultaneously makes effective response far more difficult than proactive preparation.
His perspective carries weight given Khan Academy’s mission-driven approach and extensive experience making education accessible. The organization operates as a nonprofit, suggesting Khan’s concerns stem from social impact rather than commercial interests.
The coming years will test whether voluntary corporate action, government policy, or some combination can manage AI’s workforce impact. Khan’s call for company-funded retraining represents one approach to sharing both AI’s benefits and its transitional costs across society.
