New research links AI adoption with a skills-first approach to productivity
As leaders gather in Davos to discuss the future of work, Pearson releases new findings showing that artificial intelligence alone won’t lift productivity unless paired with deliberate skilling. The research argues that AI investments yield the strongest returns when organizations invest in continuous learning and workforce development alongside the deployment of AI tools. In the United States, the combined impact could be transformative, with estimates suggesting a potential increase of up to $6.6 trillion to the economy by 2034.
Why AI needs learning to unlock real gains
The core message from Pearson is clear: AI technologies can automate routine tasks and augment decision-making, but human capital remains the deciding factor for sustained productivity. Skills modernisation—covering digital literacy, data fluency, critical thinking, and adaptability—enables employees to design, supervise, and optimize AI-driven processes. The result is not only faster outputs but higher quality work and better decision quality across industries.
Key pathways identified by the research
- <strongReskilling at scale: Employers that implement scalable skilling programs see faster AI adoption and smoother integration into workflows.
- <strongTargeted upskilling for decision-makers: Leaders equipped with analytics and AI literacy can better interpret model outputs and steer initiatives toward strategic goals.
- Continuous learning cultures: Ongoing education helps workers adapt to evolving tools, reducing the risk of skill obsolescence.
- Role redesign and task realignment: AI should automate repetitive tasks while humans focus on areas requiring creativity, empathy, and complex problem-solving.
Economic impact: up to $6.6 trillion in the US by 2034
Pearson’s analysis models a scenario where AI adoption is paired with robust skilling ecosystems. In this framework, productivity per worker rises as workers become more proficient at leveraging AI to augment their capabilities. The study notes that the financial upside isn’t solely about faster processes; it encompasses improved innovation cycles, better customer experiences, and more efficient capital allocation. The projected cumulative effect could reach $6.6 trillion, representing a meaningful acceleration in the pace of economic growth if investment in learning keeps pace with AI deployment.
Business implications and ROI considerations
For companies, the takeaway is practical: the ROI of AI investments grows when learning budgets align with technology spend. Training initiatives that accelerate AI adoption, reduce change resistance, and shorten time-to-value can substantially improve the net benefits of AI projects. Organizations that formalize skilling into project plans—with clear milestones, measurement metrics, and scalable delivery—are more likely to realize sustained productivity gains rather than one-off efficiency boosts.
What this means for the workforce
Beyond the macroeconomic outlook, the Pearson findings emphasize the worker’s experience. Professionals who view learning as a core part of their career are better prepared to navigate AI-enabled roles. Employers offering accessible training, flexible learning paths, and competency-based progression foster engagement and retention while building a pipeline of talent capable of guiding AI-driven transformations.
Conclusion: The symbiotic future of AI and learning
AI by itself speeds routines and augments judgment, but lasting productivity growth hinges on skilling and lifelong learning. Pearson’s research suggests a powerful convergence: technology plus people, trained to leverage it effectively. As firms consider where to place their next AI and training investments, they should design learning ecosystems that scale with ambition, ensuring that the productivity gains are broad, inclusive, and durable.
