Purpose: This study aims to develop a comprehensive model for digital value creation for customers in the insurance industry within the context of the digital economy. It seeks to identify key factors, strategies, and outcomes associated with digital transformation in insurance, addressing gaps in the literature on practical implementation and socio-cultural impacts. Method: This applied research adopts a qualitative methodology grounded in theory. Data were collected through semi-structured interviews with 14 insurance managers and experts in 2024, selected through purposive sampling. Additional sources included library research and specialized texts. Interviews were coded and analyzed using ATLAS. ti software, applying open, axial, and selective coding to construct the conceptual model. Findings: The analysis produced 91 initial codes, organized into 18 core concepts across six main dimensions. Causal conditions include management, technical, systemic, organizational, and human resource procedures. Contextual conditions relate to policies, laws, and the current state of the insurance industry. Intervening conditions involve financial resources, job conditions, and socio-cultural factors. Strategies identified include incentive policies, training and specialization, digitization, and strategic review. The outcomes highlight improved industry efficiency, better customer management, enhanced employee satisfaction, and stronger project management. Conclusion: The proposed model underscores the importance of continuous adaptation to technological change and market dynamics for success in the digital economy. Key recommendations include implementing automation systems, applying AI for personalized services, strengthening data security, and advancing digital communication channels. This model provides a strategic framework for insurance companies to enhance digital value creation, improve customer experience, and achieve sustainable growth in a competitive environment.