Bank of America’s research team argued AI’s eventual productivity impact could be far larger than what the economy is currently showing, framing the gap around a small estimated aggregate lift. The bank’s report highlights a roughly 0.1% productivity contribution estimate now—while noting task-level gains in areas like coding and customer support. The report’s core issue is diffusion and economics: AI can transform only a subset of workplace tasks, and only a fraction are cost-effective to automate at current prices. The bank says macro-level GDP statistics can miss quality improvements, but it still points to a mismatch between micro-level tool performance and measured aggregate outcomes. For higher education, the research feeds planning conversations about how quickly AI tools translate into measurable learning, research throughput, and institutional productivity—especially as faculty and administrators ask for evidence that investments improve outcomes.