Quality models are falling behind—AI, digital shifts demand urgent upgrade
Swedish organizations are outpacing traditional excellence frameworks, prioritizing AI integration, digital transformation, and workforce reskilling that current quality standards don't adequately address. Business leaders face a critical gap: existing excellence models lack the tools to handle rapid change, threatening competitiveness and organizational resilience.
Originaltitel: Future research on quality management and development needs for excellence models
<p>The purpose of this paper is to identify and explore important emerging organizational challenges from a quality management (QM) perspective and investigate how current excellence models incorporate these challenges. The paper is based on a Delphi study of Swedish organizations. 54 challenges were generated and ranked according to importance and the ten top-ranked challenges were compared to four excellence models. Both public and private organizations face growing demands for competence development, digital transformation, innovation, and adaptability, requiring a shift beyond traditional excellence models. The public sector prioritizes governance and learning culture, while the private sector focuses on agility and technology integration. To remain relevant, excellence models must evolve to further incorporate AI, digitalization, sustainability, and employee engagement, ensuring resilience and strategic adaptability in a rapidly changing environment. The findings point to several specific avenues for future research in Quality Management (QM). As organizations face growing demands for digitalization, AI integration, and workforce reskilling, future studies should explore how QM models can more effectively support technological adaptation and continuous competence development. Research is also needed on how QM can facilitate cross-organizational collaboration and enable more agile, innovation-driven cultures.</p>