Core Insights - The economic potential of AI can be significantly enhanced by pairing technology investment with continuous learning, potentially adding between $4.8 trillion and $6.6 trillion to the U.S. economy by 2034, which is about 15% of the current U.S. GDP at the lower estimate [1][2] Group 1: AI and Productivity - Companies are investing billions in AI infrastructure, but there are limited examples of productivity gains that benefit workers and drive return on investment [2] - The current focus on replacing workers with AI creates uncertainty in workplaces, while the broader economic uplift from AI remains elusive [2][3] - A critical "learning gap" is identified as the main barrier preventing full utilization of AI's potential by both employers and employees [2][4] Group 2: Human Skills and AI Adoption - The lack of human skills to work alongside AI technologies is seen as the biggest obstacle to successful AI adoption [3] - Addressing the skills gap is essential for supporting workers, boosting their confidence, and achieving desired ROI outcomes for businesses [3][4] - According to the World Economic Forum, 59% of the global workforce will require reskilling by 2030, highlighting the urgency of addressing the learning gap [4] Group 3: Learning Framework - Pearson's report proposes a new approach to workplace learning that integrates technology deployment with skill building, termed the DEEP Learning Framework [4][6] - The framework includes actionable steps such as diagnosing task-level augmentation plans and embedding learning into the workflow [6] - Employers risk missing productivity gains if they focus solely on technology deployment without considering the human aspect of AI adoption [4]