AI's learning gap gets multi trillion dollar price tag
Economic modelling finds that AI alone will not deliver expected productivity gains, with learning and skills development identified as the key constraint on value, potentially worth up to $6.6 trillion to the US economy, around a quarter of GDP, by 2034.
The productivity gains promised by artificial intelligence will not be realised without faster investment in learning, according to new research from Pearson, which estimates that pairing AI deployment with skills development could add between $4.8 trillion and $6.6 trillion to US GDP over the next decade.
Released at the World Economic Forum in Davos, the report finds that AI adoption has moved faster than organisations’ ability to equip people with the skills needed to use the technology effectively. As a result, technology investment on its own is falling short of the productivity and return on investment many employers expect.
The research argues that the strongest gains come from augmenting jobs with AI rather than focusing primarily on workforce replacement. Where AI deployment is paired with continuous learning and clearer task design, productivity gains are more likely to translate into economic value.
‘Every positive scenario for this AI-enabled future is built on human development,’ said Omar Abbosh, chief executive of Pearson. ‘The biggest obstacle to AI adoption is the lack of human skills to work alongside these technologies.’
The report finds that while AI capability has advanced rapidly, learning systems have not kept pace. Roles, expectations and skills development often lag behind how work is changing, leaving employees to adapt informally as tools evolve. Even where adoption is widespread, this limits the value organisations can extract.
Pearson argues that learning should be embedded directly into AI deployment rather than treated as a follow-on activity. Its framework focuses on understanding how tasks change, building skills alongside technology rollout, measuring progress and treating learning as a strategic investment.
As AI continues to scale across organisations, the constraint on productivity is shifting. The limiting factor is no longer tool capability but how quickly people can develop the skills needed to use AI effectively. Where learning falls behind, faster tools increase activity without improving outcomes.
Key facts
- New research finds that AI productivity gains depend on learning, not technology deployment alone.
- The study estimates that pairing AI with continuous learning could add between $4.8 trillion and $6.6 trillion to the US economy by 2034.
- Equivalent to up to a quarter of current US GDP.
- Research argues that AI adoption has outpaced workforce skills development, limiting return on investment.
- Stronger outcomes are associated with augmenting jobs with AI rather than replacing workers.
- Employers risk accelerating activity without improving productivity if learning does not keep pace with AI deployment.
- Findings released at the World Economic Forum.
Download the report
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