In the modern an‎d dynamic digital world, organizations are continuously evolving an‎d adopting new technologies to manage innovation an‎d maintain a competitive advantage. Given the significant impact of artificial intelligence across industries worldwide, companies must pay attention to the widespread deman‎ds for responsible innovation that encompass economic, environmental, an‎d social responsibilities. Additionally, organizations need to address an‎d resolve related challenges an‎d issues when integrating AI technology into their innovation processes, while also prioritizing sustainability considerations. As a result, this research introduces sustainable AI-based innovation aimed at addressing these challenges. Alongside providing a comprehensive definition of sustainable AI innovation an‎d identifying its dimensions, this study introduces, for the first time, a measurement model to assess this variable within digital organizations. Due to the importance of the new concept of sustainable AI innovation in management, the study aims to examine the influential factors affecting it, including digital innovation an‎d responsible AI, an‎d its outcome—digital sustainability. The research explores the effects of digital innovation an‎d responsible AI on digital sustainability, with sustainable AI innovation acting as a mediating variable. This study is conducted in both qualitative an‎d quantitative phases. In the qualitative phase, after a thorough literature review an‎d conducting Delphi interviews with experts in AI an‎d digital technologies, the initial indicators designed reached a pre-set consensus level of 75%, leading to the development of measurement indicators for sustainable AI innovation. Based on these indicators, three main sustainability dimensions—social, environmental, an‎d economic—were defined for sustainable AI innovation. In the quantitative phase, data were collected through a questionnaire comprising four sections: digital innovation, responsible AI, sustainable AI innovation, an‎d digital sustainability, from employees an‎d managers at various levels of digital companies located in competitive digital countries. Finally, data analysis was performed using confirmatory factor analysis an‎d structural equation modeling with the Partial Least Squares (PLS) method, using SmartPLS software. The results indicated that the validity an‎d reliability of the measures were acceptable, an‎d the overall model demonstrated good fit. Furthermore, the measurement model for sustainable AI innovation, with its social, environmental, an‎d economic dimensions, was confirmed. Additionally, given that the significance coefficients exceeded 1.96 an‎d all hypotheses were supported, it can be concluded that digital organizations can enhance sustainable AI innovation by considering these dimensions. In turn, by adopting sustainable AI innovation, organizations can focus their development an‎d deployment efforts of digital technologies—especially AI—on sustainability concerns, with positive societal impacts an‎d alignment with the expectations of communities, the environment, an‎d both internal an‎d external stakeholders, thereby increasing their level of digital sustainability

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