AI is producing large productivity improvements in specific workplace tasks, including software development, customer support, and writing. Despite these micro-level gains, they have not translated into a clear boost to GDP. Only a portion of workplace tasks can be automated cost-effectively at current prices, and automated work reduces labor costs by a limited amount. Labor represents about half of total costs, so the implied ceiling for labor productivity gains is constrained. Organizational friction, skills mismatches, slow diffusion, and regulatory drag further reduce realized gains. The resulting estimate is around 0.1% per year, while the broader economic impact remains uncertain.
"AI is already delivering task-level productivity gains that would have seemed implausible five years ago: software developers completing 55% more work with AI coding tools, customer support agents resolving 14% more tickets, professional writers finishing projects 37% to 40% faster."
"while AI can currently transform about 20% of all workplace tasks, only 23% of those are actually cost-effective to automate at today's prices. Automated tasks save roughly 27% in labor costs, and labor is about half of all costs. Multiply it out and the theoretical ceiling is a 0.66% gain in labor productivity - before organizational friction, skills mismatches, slow diffusion, and regulatory drag compress it further toward the figure BofA has landed on: 0.1% per year."
"The problem is that the economy is currently showing 0.1%, "a small aggregate effect relative to all the excitement around AI," the bank admitted. It's a number so small that it barely registers against global growth of 3.5%."
"The bank acknowledges the academic literature on AI's aggregate impact is "inconclusive," with multiple studies finding that even firm-lev"
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