Zahra Haghighi Aghdam

As artificial intelligence (AI) continues to reshape creative industries, design management is facing critical transformation. Despite growing interest in human-AI collaboration, current literature lacks a comprehensive and structured understanding of how socio-technical, cognitive, ethical, and organizational factors interact in design environments. Most existing studies either focus on isolated aspects such as algorithmic efficiency or ethical guidelines, while overlooking dynamic interplay among cultural, participatory, and managerial dimensions essential to human-centered innovation. Addressing this gap, the present study proposes and validates an interpretive structural model that maps the hierarchical interrelations among twelve key dimensions of AI-human collaboration in design management, grounded in the principles of Industry 5.0. The novelty of this research lies in its dual-layered methodology. It integrates interpretive structural modeling and MICMAC analysis with real-world validation through a case study involving a multidisciplinary design team. The results not only reveal foundational drivers such as Human-AI Co-Creation Culture and Human-Centered Value Integration but also highlight the dynamic roles of Explainability, Agile Management, and Organizational Readiness. Notably, the model was refined based on empirical insights, introducing new relational pathways and feedback loops that enhance its practical applicability. The findings demonstrate that successful AI-human collaboration requires a layered ecosystem of trust, transparency, cultural alignment, and adaptive capacity. This study contributes a validated, actionable framework that guides both researchers and practitioners in implementing ethical, effective, and scalable AI-assisted design strategies. By bridging conceptual modeling and field-based validation, it offers a significant step forward in operationalizing the values of human-centered design in AI-integrated environments.

Design management in Industry 5.0 faces a persistent gap due to fragmented conceptualizations that treat AI, human creativity, and machine capabilities as largely separate elements, limiting their effective integration within complex socio-technical systems. Addressing this gap, the present study develops and empirically validates a Design Management Model grounded in human-centered, ethical, and sustainability-oriented principles, framing design management as an adaptive and relational system rather than a linear or technology-driven process. Departing from the automation-oriented logic of Industry 4.0, the study adopts an augmented cognition perspective in which AI functions as a collaborative partner supporting, rather than replacing, human judgment. A sequential mixed-methods approach was employed, integrating systematic literature review, qualitative content analysis, expert evaluation, and Structural Equation Modeling (SEM) based on data from 316 participants, followed by empirical examination in two service-oriented case contexts, namely tourism/hospitality and healthcare services. The findings identify and validate six interrelated domains and demonstrate that Human–AI–Machine Synergy plays a central role in shaping design outcomes. More specifically, the results show that effective design management in Industry 5.0 depends on the coordinated interaction between cognitive processes, technological infrastructures, and organizational strategies, rather than on isolated technological advancement. Empirical applications further illustrate how the model supports ethically guided AI integration, enhances adaptive decision-making, and improves experience-oriented innovation across different contexts. By providing a validated structural framework that connects previously disjointed elements, this study contributes a clearer operational understanding of how human–AI collaboration can be embedded within design management practices in Industry 5.0.