Managing generative AI as organizational change: evidence from a multi-institutional study in education

Purpose This paper presents findings from a 1.5-year multi-institutional study on the integration of Generative Artificial Intelligence (GenAI) into educational institutions under the Vienna Chamber of Commerce and Industry (WKW). Grounded in Luhmann’s social systems theory, the study conceptualizes GenAI integration as a challenge of organizational programming, requiring a shift from conditional (rule-based) to purposive (goal-oriented) approaches that accommodate technological uncertainty while fostering competency development. With the rapid rise of GenAI, educational institutions are facing a major organizational change that challenges established structures and routines and requires purposeful adaptation. Design/methodology/approach A mixed-methods design was applied across four institutions spanning secondary, vocational, tertiary, and adult education. The empirical study combined a large-scale learner survey (n = 1,577), educator focus groups (n = 23), and controlled experiments (n = 47) comparing student teams with and without access to GenAI. Findings Six critical success factors were identified. Beyond technical skills, outcomes depended on: (1) clear communication and role definition, (2) shared responsibility and team cohesion, (3) prior GenAI experience, (4) critical reflection on AI-generated content, (5) intrinsic motivation, and (6) capacity for innovative thinking. Strong teamwork yielded superior results regardless of AI use; unstructured AI adoption consistently weakened outcomes. Findings informed the establishment of a KI-Info-Hub, a centralized digital platform providing educators with access to training materials and evidence-based practices. Originality/value This study offers one of the first comprehensive, practice-based evaluations of GenAI in German-speaking vocational and higher education and provides actionable strategies for competency-oriented, human-centered GenAI integration.