Faculty of Entrepreneurship, University of Tehran Journal of Entrepreneurship Development 2008-2266 17 4 2025 01 20 The Effect of Artificial Intelligence Adoption on Social Sustainability (Case Study: Isfahan Province Knowledge-Based Companies) The Effect of Artificial Intelligence Adoption on Social Sustainability (Case Study: Isfahan Province Knowledge-Based Companies) 1 31 99967 10.22059/jed.2024.381974.654410 FA Tinasadat Mahmoudi Department of Management, Faculty of Economics, Management and Social Sciences, Shiraz University, Shiraz, Iran 0009-0008-5973-4355 Mohammad Hossein Ronaghi Department of Management, Faculty of Economics, Management and Social Sciences, Shiraz University, Shiraz, Iran Alireza Amini Department of Management, Faculty of Economics, Management and Social Sciences, Shiraz University, Shiraz, Iran Journal Article 2024 09 06 Objective: Social sustainability is a process for creating sustainable successful places that promote wellbeing, by understanding what people need from the places they live and work. Social sustainability combines design of the physical realm with design of the social world – infrastructure to support social and cultural life, social amenities, systems for citizen engagement, and space for people and places to evolve. That Artificial Intelligence (AI) can be used as a tool for environmental and climate action is today evident. AI has a great potential to assess, predict, and mitigate the effects of climate change as it gathers, interprets, and completes large and complex datasets on emissions and climate impact, which provides better solutions for informed decision-making. Artificial intelligence systems are complex socio-technical–ecological systems that are associated with multiple social, environmental, and economic challenges. Current discussions raise the question of whether AI systems impede or support a social and ecologically just society. Given the widespread impact of artificial intelligence technology in improving efficiency, increasing innovation, and enhancing decision-making quality in companies, this technology can play a significant role in promoting social sustainability. Therefore, the aim of this research is to evaluate the impact of adopting this technology on social sustainability in knowledge-based companies in Isfahan Province. <br /><br />Method: This research is developmental-applied in terms of its purpose and qualitative-quantitative in terms of its study approach. In terms of its nature, it is a mixed exploratory study with a cross-sectional time horizon. To collect data in the qualitative section, a systematic literature review was used, and through content analysis, 10 components (effort expectancy, performance expectancy, social influence, facilitating conditions, trust, privacy and security, work condition, work environment, work safety, and skill development) related to the factors influencing the adoption of artificial intelligence on social sustainability emerged. In the next part, considering the sample size for the population according to Morgan's table, 74 researcher-made questionnaires were completed and collected with the participation of managers of knowledge-based companies in Isfahan Province who are active in the field of information and communication technology. Then, in order to implement the structural equation modeling method, the data was analyzed using the Smart PLS software, and the influential indicators in the adoption of artificial intelligence on social sustainability were classified at four levels, and a power-dependency diagram was drawn for them.<br /><br />Conclusion: The research findings show that the performance expectancy component is the most effective and influential indicator among the factors influencing the adoption of artificial intelligence on social sustainability, which has a significant impact on other components and therefore should be given more attention. Also, the most affected factors with low driving power are the work environment, social influence, effort expectancy, and facilitating conditions. Finally, the increased use of Artificial intelligence systems (AI systems) is associated with multifaceted social, environmental, and economic consequences. Objective: Social sustainability is a process for creating sustainable successful places that promote wellbeing, by understanding what people need from the places they live and work. Social sustainability combines design of the physical realm with design of the social world – infrastructure to support social and cultural life, social amenities, systems for citizen engagement, and space for people and places to evolve. That Artificial Intelligence (AI) can be used as a tool for environmental and climate action is today evident. AI has a great potential to assess, predict, and mitigate the effects of climate change as it gathers, interprets, and completes large and complex datasets on emissions and climate impact, which provides better solutions for informed decision-making. Artificial intelligence systems are complex socio-technical–ecological systems that are associated with multiple social, environmental, and economic challenges. Current discussions raise the question of whether AI systems impede or support a social and ecologically just society. Given the widespread impact of artificial intelligence technology in improving efficiency, increasing innovation, and enhancing decision-making quality in companies, this technology can play a significant role in promoting social sustainability. Therefore, the aim of this research is to evaluate the impact of adopting this technology on social sustainability in knowledge-based companies in Isfahan Province. <br /><br />Method: This research is developmental-applied in terms of its purpose and qualitative-quantitative in terms of its study approach. In terms of its nature, it is a mixed exploratory study with a cross-sectional time horizon. To collect data in the qualitative section, a systematic literature review was used, and through content analysis, 10 components (effort expectancy, performance expectancy, social influence, facilitating conditions, trust, privacy and security, work condition, work environment, work safety, and skill development) related to the factors influencing the adoption of artificial intelligence on social sustainability emerged. In the next part, considering the sample size for the population according to Morgan's table, 74 researcher-made questionnaires were completed and collected with the participation of managers of knowledge-based companies in Isfahan Province who are active in the field of information and communication technology. Then, in order to implement the structural equation modeling method, the data was analyzed using the Smart PLS software, and the influential indicators in the adoption of artificial intelligence on social sustainability were classified at four levels, and a power-dependency diagram was drawn for them.<br /><br />Conclusion: The research findings show that the performance expectancy component is the most effective and influential indicator among the factors influencing the adoption of artificial intelligence on social sustainability, which has a significant impact on other components and therefore should be given more attention. Also, the most affected factors with low driving power are the work environment, social influence, effort expectancy, and facilitating conditions. Finally, the increased use of Artificial intelligence systems (AI systems) is associated with multifaceted social, environmental, and economic consequences. https://jed.ut.ac.ir/article_99967_6d9e4a65ea62abcaf441f3ef9b3730df.pdf