TechCapsules

AI-summarised brief · reviewed before publication

Microsoft CEO Satya Nadella has been quoted as saying, "The hardest part of AI isn’t the tech - it's getting people to change how they work." This statement resonates deeply in the current landscape of corporate AI adoption. Daily AI usage by employees has doubled in the past 12 months, rising from 4% to 8% of employees. While this growth may seem promising, it also highlights that a staggering 92% of employees still do not use AI daily, despite the substantial investments and hype surrounding the technology. However, this statistic belies a fundamental truth. Corporate AI adoption is not just about implementing the technology, but about driving change in how employees work. According to the PwC 2025 Global AI Jobs Barometer, since the proliferation of generative AI in 2022, global productivity growth has nearly quadrupled in industries most exposed to AI, such as financial services and software publishing, rising from 7% from 2018-2022 to 27% from 2018-2024. In contrast, the rate of productivity growth in industries least exposed to AI, such as mining and hospitality, has declined from 10% to 9% over the same period. This underscores the importance of driving AI adoption within organizations. It is no longer a question of if companies should adopt AI, but rather how they can effectively implement it to drive productivity growth. While a large majority (78%) of respondents say their organizations use AI in at least one business function, according to McKinsey's latest State of AI report, the success or failure of this technology ultimately relies on its adoption by employees. This is a fundamental principle in business transformation that consulting firms have studied for decades and have created countless presentations and papers to help enterprises with organizational change. A closer examination of the data reveals a more nuanced story. Despite two years of AI hype, only 8% of U.S. employees use AI daily, up from a tiny fraction just a year ago. The challenge ahead lies in bridging this gap and driving AI adoption across all levels of an organization.