Generative Artificial Intelligence (AI) tools like ChatGPT offer significant potential in the corporate world and organizational leadership. Organizations are actively integrating Generative AI (GenAI) into their operations to leverage its benefits. However, research is yet to explore the factors supporting the continuity of GenAI-powered Optimization Intelligence (GenAI-OI) processes in organizational contexts. This study seeks to address this gap by focusing on the challenges of standardizing such optimization intelligence systems. It utilizes the Normalization Process Theory (NPT) to facilitate a theoretical exploration of this standardization process. From both a research and practical standpoint, it elucidates how NPT can be applied to provide a structured framework for understanding and theorizing the processes involved in embedding and sustaining GenAI-OI systems, which play a pivotal role in shaping the future of organizational agility. This research endeavors to uncover valuable insights for organizations seeking not only to adopt but sustain this technology effectively.

As an emerging technology, Generative Artificial Intelligence (AI) holds immense potential for application across various levels of business and management. However, current studies have not yet investigated the elements that impact the acceptance and implementation of generative AI tools, such as ChatGPT, within organizational settings. To fully leverage its benefits, organizations must embrace and integrate Generative AI at a comprehensive and profound level, making it a valuable area of study. This study aims to put forth and examine the influencing factors impacting the adoption of generative AI technology by utilizing the Technology-Organization-Environment framework in conjunction with the institutional theory and the diffusion of innovation theory. Data from 108 organizations in India is collected and analyzed, leading to valuable insights and implications that contribute to a deeper understanding of the key determinants of generative AI adoption. The study digs out valuable knowledge for organizations looking to embrace this technology.

Businesses are increasingly preparing for remote working by equipping managers and their teams with the necessary tools and technology. This research focuses on understanding how technology–enabled remote working practices are implemented and normalized, taking into consideration the context in which they are applied. By utilizing process virtualization theory (PVT) to quantitatively evaluate context-dependent factors and normalization process theory (NPT) to explore the normalization of new technology-driven remote work practices, this study investigates the static and dynamic factors affecting the virtualization of remote work processes, as well as their implementation and normalization. The results from multiple surveys reveal that sensory requirements along with relationship requirements and control requirements are dynamic factors that are driven by the context and enable the technology–enabled virtualization of remote work processes. Furthermore, the relative normalization of this work transformation is sustained through flexible co–construction, legitimation, contextual integration, and effective leadership.