Economist Steve Hanke Warns High Costs Prevent AI from Replacing Human Labor at Scale

Johns Hopkins economist Steve Hanke argued that AI's high resource consumption and marginal costs make it unlikely to replace human labor at scale, challenging the belief that AI services will eventually become virtually free. He noted that unlike traditional software, AI incurs ongoing computing and physical resource costs for every query it processes. This perspective challenges the prevailing tech industry narrative of AI-driven hyper-efficiency and job displacement by highlighting the massive capital expenditures required for AI infrastructure. It underscores growing skepticism among economists and investors regarding the long-term return on investment for AI technologies. Major tech companies are projected to spend $700 billion this year and up to $1 trillion by 2027 on AI data centers and hardware like GPUs. Hanke emphasized that AI requires continuous inputs of water, electricity, and physical capital, making the cost of using AI higher than employing humans in many scenarios.