Grassroots AI integration in organizations: from employee initiative to institutional learning

Purpose This viewpoint explores how artificial intelligence (AI) adoption increasingly emerges as a grassroots movement within organizations. It argues that employees’ informal experimentation with AI tools reshapes organizational learning, development practices, and governance models. Design/methodology/approach Drawing on recent organizational learning and management literature, this paper adopts a conceptual and practice-oriented perspective. It interprets emerging workplace trends to provide actionable insights for leaders, managers, and trainers navigating AI-enabled change. Findings Drawing on recent organizational learning and management literature, this paper adopts a conceptual and practice-oriented perspective. It interprets emerging workplace trends to provide actionable insights for leaders, managers, and trainers navigating AI-enabled change. Research limitations/implications Organizations should legitimize grassroots AI initiatives, establish safe communication channels, and build adaptive training strategies. Managers are encouraged to act as facilitators rather than gatekeepers, translating informal AI use into institutional knowledge and policy learning. Practical implications Organizations should legitimize grassroots AI initiatives, establish safe communication channels, and build adaptive training strategies. Managers are encouraged to act as facilitators rather than gatekeepers, translating informal AI use into institutional knowledge and policy learning. Originality/value This paper reframes AI integration as a bottom-up learning phenomenon rather than a purely technological or managerial process. It contributes to ongoing discussions in Development and Learning in Organizations by highlighting how grassroots experimentation can serve as a driver of institutional innovation and cultural agility.