Designing an AI-Based Model for Generation Z Online Employee Productivity with a Grounded Theory Approach

Purpose: In the current era, where advanced digital technologies and artificial intelligence serve as pivotal drivers of change in organizational structures and work processes, Generation Z, as the youngest cohort in the workforce, plays a crucial and decisive role in enhancing organizational productivity. This generation, having grown up immersed in advanced technologies and digital environments, exhibits distinct behavioral traits, needs, and work patterns that are incompatible with traditional management approaches and therefore require innovative and specialized strategies. Accordingly, the objective of this study is to design and develop a comprehensive and practical scientific model aimed at improving the performance and increasing the productivity of online Generation Z employees in AI-driven work environments. The proposed model endeavors to provide an adaptive framework by precisely identifying the factors influencing motivation, job satisfaction, technological competencies, and digital interactions of this generation, maximizing their capabilities and turning emerging challenges into transformative opportunities. Ultimately, this model aims to offer a scientific and practical foundation for organizational managers and human resource professionals to foster sustainable development and success in the digital transformation era through enhanced productivity and greater job satisfaction.
Methodology: The present study employs a qualitative, applied, and exploratory research design a imed at gaining a deep and comprehensive understanding of online employee productivity among Generation Z based on artificial intelligence. The research population consisted of online Generation Z employees who directly interact with AI technologies in their work environments. Samples were selected through purposive sampling to ensure that participants possessed the necessary expertise, sufficient experience, and direct relevance to the research topic, thereby enabling the collection of relevant and precise data. Data collection was conducted through semi-structured interviews with 13 experts, including Generation Z employees and specialists in the field of artificial intelligence. This interview approach allowed for the in-depth exploration of topics and the extraction of rich and diverse qualitative data. Following data collection, a systematic and staged data analysis was performed during which key concepts and categories were identified and coded. During the analysis process, special attention was given to the iterative examination and comparison of emerging concepts to develop a coherent framework consisting of causal factors, contextual elements, intervening variables, strategies, and outcomes related to Generation Z employee productivity. These analyses led to the formulation of a comprehensive model that addresses various dimensions of the topic and is applicable to online work environments. Thus, by employing purposive sampling, semi-structured interviews, and rigorous qualitative data analysis, the present research has produced reliable scientific and practical findings regarding Generation Z’s productivity based on artificial intelligence.
Results: The present study employs a qualitative, applied, and exploratory research design aimed at gaining a deep and comprehensive understanding of online employee productivity among Generation Z based on artificial intelligence. The research population consisted of online Generation Z employees who directly interact with AI technologies in their work environments. Samples were selected through purposive sampling to ensure that participants possessed the necessary expertise, sufficient experience, and direct relevance to the research topic, thereby enabling the collection of relevant and precise data. Data collection was conducted through semi-structured interviews with 13 experts, including Generation Z employees and specialists in the field of artificial intelligence. This interview approach allowed for the in-depth exploration of topics and the extraction of rich and diverse qualitative data. Following data collection, a systematic and staged data analysis was performed during which key concepts and categories were identified and coded. During the analysis process, special attention was given to the iterative examination and comparison of emerging concepts to develop a coherent framework consisting of causal factors, contextual elements, intervening variables, strategies, and outcomes related to Generation Z employee productivity. These analyses led to the formulation of a comprehensive model that addresses various dimensions of the topic and is applicable to online work environments. Thus, by employing purposive sampling, semi-structured interviews, and rigorous qualitative data analysis, the present research has produced reliable scientific and practical findings regarding Generation Z’s productivity based on artificial intelligence.
Discussion: This research is distinguished by its originality and innovation due to the design of the first productivity model for online Generation Z employees based on artificial intelligence, utilizing a grounded theory approach. The value of this study is highlighted in several dimensions. First, it provides a scientific and practical framework tailored to the specific characteristics and needs of Generation Z in online work environments, serving as a foundation for improving performance and human resource management in the era of advanced technologies. Second, the use of a qualitative grounded theory method combined with modern data analysis tools such as MAXQDA and Visio has enhanced the precision and depth of the analysis, leading to the identification of key productivity factors that have been less explored in this field. Moreover, this model serves as a strategic tool for organizations, not only increasing job satisfaction and skill development among Generation Z but also delivering outcomes such as task automation, improved quality and productivity, and enhanced competitiveness. Ultimately, this study can act as a starting point for future research and the development of innovative management policies in the domain of the digital workforce and new generations, significantly contributing to the sustainable growth of online businesses.
Conclusion: Considering the rapid development of modern technologies, especially artificial intelligence, Generation Z as a cohort raised in the digital age holds unique expectations and needs regarding the application of technology in work environments. This study, employing a grounded theory approach and qualitative analysis, presents a comprehensive model of online employee productivity for Generation Z based on artificial intelligence, encompassing causal factors, contextual elements, intervening variables, strategies, and outcomes. The findings indicate that Generation Z possesses a positive outlook on artificial intelligence and its impact on alleviating repetitive tasks, enhancing work quality, developing skills, and fostering professional growth. Moreover, AI helps them perform work processes more simply and accurately, reducing their workload, which in turn leads to increased job satisfaction and organizational productivity. Despite these advantages, challenges and concerns such as fear of job displacement, decreased human interaction, and ethical issues are also observed among Generation Z. Addressing these requires education, cultural development, and change management. Furthermore, intervening factors like internet limitations, data security, and cultural and economic considerations play a crucial role in the acceptance and effectiveness of artificial intelligence, and managing these factors is essential for achieving optimal productivity. Additionally, organizational contextual factors such as flexible structures, advanced technological infrastructures, effective training programs, and an innovative culture provide a foundation for the successful implementation of AI in Generation Z’s work environments. The strategies designed within the model focus on simplifying technology use, developing employees’ specialized skills, fostering motivation, and removing obstacles, all of which play a decisive role in enhancing Generation Z’s productivity and job satisfaction. Ultimately, the outcomes of leveraging artificial intelligence include task automation, improved accuracy and quality, professional development and innovation, enhanced communication, and increased organizational competitiveness. Collectively, these signify a profound transformation in Generation Z’s online work environments in the era of smart technologies. This model can serve as both a practical and scientific guide for organizations in managing Generation Z’s workforce and achieving sustainable development in online businesses.