Validation of the AI-Readiness and Market Dynamics Disruption Index (AIM-DDI) Framework: A Case Study of Its Application in the Beauty Cluster


== Abstract ==

The adoption of artificial intelligence (AI) is transforming and disrupting industries by driving innovation, enhancing operational efficiency, and reshaping market dynamics. However, organizations often struggle to balance internal readiness with external market alignment, creating a critical need for comprehensive frameworks to guide AI integration. This study introduces and validates the AI-Readiness and Market Dynamics Disruption Index (AIM-DDI), a holistic tool for evaluating organizational AI maturity. By combining internal factors, such as strategy, talent, and governance, with external elements, including customer expectations, industry disruption potential, and regulatory environments, the AIM-DDI provides actionable insights for navigating AI-driven transformation. The research validates the AIM-DDI scale and questionnaire, leveraging data from 765 organizations to identify distinct AI maturity profiles. Cronbach’s Alpha Analysis , Exploratory and Confirmatory Factor Analyses confirm the framework’s validity, while cluster analysis reveals strategic pathways for organizations at various stages of AI readiness. The findings highlight the importance of aligning internal capabilities with external pressures to achieve competitive advantage and sustainable growth. We also apply the AIM-DDI framework within the Beauty Clusters Industry Association in Spain data as business case. This study offers valuable contributions for academics, practitioners, and policymakers aiming to leverage AI as a driver of industry evolution.

== Full document ==
<pdf>Media:Draft_Congres2025_446368756-1080-document.pdf</pdf>