New research from Pearson suggests that artificial intelligence alone will not deliver the productivity gains businesses and economies expect unless it is paired with sustained investment in workforce learning. Released at the World Economic Forum Annual Meeting in Davos, the report argues that skilling is the missing ingredient in realizing AI’s economic promise.
Titled “Mind the Learning Gap: The Missing Link in AI’s Productivity Promise,” the study finds that using AI to augment jobs-rather than as a replacement for workers-could add between $4.8 trillion and $6.6 trillion to the US economy by 2034. At the high end, that equates to roughly 15% of current US GDP. But those gains are contingent upon employees having the skills to work effectively alongside AI systems.
As Pearson mentions, despite billions that flowed into AI models and infrastructure, tangible productivity improvements remain limited across most industries, with software development being a notable exception. While workers frequently report time saved from using AI tools, the research highlights a broader “learning gap” preventing organizations from translating efficiency into meaningful economic value and return on investment.
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“AI will drive profound long-term change to business and industry. But leaders are under pressure to rapidly adopt AI and demonstrate a return on that investment, all while bringing worried employees along with this seismic shift. Every positive scenario for this AI-enabled future is built on human development,” said Pearson CEO Omar Abbosh. “As a learning company, we see that the biggest obstacle to AI adoption is the lack of human skills to work alongside these technologies. Addressing that will support workers, boost their confidence with new technology, and drive the ROI outcomes that businesses want.”
To help organizations close this gap, Pearson outlines a new DEEP Learning Framework that calls on leaders to align technology deployment with skills development. The approach emphasizes diagnosing tasks suited for AI augmentation, embedding learning into daily workflows, measuring skills progress, and treating learning as a core strategic investment.
With AI adoption accelerating faster than workforce reskilling, Pearson’s findings reinforce a growing consensus: without learning at the center of AI strategy, the promised productivity revolution is unlikely to materialize.
