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His recently published 90-page report provides a detailed view of the evolution of GenAI in organizations over the past three years (2023 through 2025). At a high level, the evolution can be described as: 2023 (Exploration): Initial curiosity, cautious use for simple tasks. 2024 (Experimentation): Increased pilots, focus on proving value. 2025 (Accountable Acceleration): Integration into core operations, ROI measurement, risk mitigation, and talent development. The study, now in its third year, is sponsored by Wharton Human-AI Research, part of the Wharton AI & Analytics Initiative at the Wharton School, University of Pennsylvania; GBK Collective performed the research and analysis. The cross-sectional study covers various topics, ranging from where the common use cases are, where returns are emerging, and which people and process-levers could convert mainstream use into sustainable ROI. Page 56 begins a section titled The Human Capital Lever: Aligning Talent, Training & Trust. One interesting chart on page 60 shows that while AI is enhancing employees’ skills in some tasks, there are concerns about skills atrophy (declines in employees’ skill proficiency). Given the breadth of this report, readers will need to dig into it to explore its many insights. As a bonus, you can check out a working paper by researchers at Harvard Business School and Stanford University titled, The GenAI Wall Effect: Examining the Limits to Horizontal Expertise Transfer Between Occupational Insiders and Outsiders. It shows that while GenAI helps bridge expertise gaps, it eventually reaches a point where it can no longer meaningfully narrow the gap between occupational insiders and outsiders. One implication is that domain knowledge and contextual understanding remain essential for interpreting GenAI-enabled output.
