International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 13 Issue: 08 | Aug 2026
p-ISSN: 2395-0072
www.irjet.net
Socio-Technical Factors Influencing Generative AI Adoption: An Empirical Study of Employee Productivity and Operational Efficiency in IT Service Firms Mandar Anil Dumbre Independent Researcher, Pune, Maharashtra, India ----------------------------------------------------------------------------***----------------------------------------------------------------------------
Abstract-GenAI is being incorporated into the processes
The IT services sector is one of the early adopters of Generative AI technology. Tools such as GitHub Copilot, large language models for enterprise use, intelligent documentation tools, and conversational assistants are becoming common in software development, testing, project management, and technical support processes. This technology can lead to a reduction in repetitive tasks, improvement in the quality of software development, faster project delivery, and employee productivity.
of IT service providers for tasks such as software development, technical writing, testing, and knowledge management. Though these technologies present opportunities for organizational effectiveness, there are huge differences between the results obtained from using them in various organizations. Such differences indicate that effective use of GenAI depends not only on technology but also on other factors. This study will investigate the socio-technical factors that affect the acceptance of generative artificial intelligence (AI) among IT services organizations. The technology acceptance model will be used as the central theory for this research and will be expanded through the inclusion of management support, employee training, and reliability of AI tools as organizational factors of technology adoption. A mixed methodology will be employed involving a structured questionnaire using a Likert scale. This research assesses the effect of the above-listed factors on the level of perceived usefulness, perceived ease of use, employee productivity, efficiency, and job satisfaction. The research asserts that realization of sustainability through Generative AI depends on the successful integration of the technology with the help of efficient leadership, development of employees' capabilities, and organizational readiness. The results of the research will be useful for understanding the process of AI adoption in knowledge-based organizations.
Nevertheless, the effective application of Generative AI depends on other factors aside from technical expertise. Organizational leaders have to see to it that the employees are sufficiently skilled in using AI technology and receive proper guidance, and that AI technology is integrated into the business process in such a way that it supports organizational goals. This explains why the application of Generative AI involves both technical and organizational changes. 1.2 Business Context Over time, the IT service company business model depended on hiring more people in order to increase its capacity for operations. With an increasing demand for projects, organizations would hire more people to deliver on these demands. This led to a correlation between the growth of the organization and the number of people hired. While this business model helped organizations expand their business predictably, it also increased costs of operations.
Keywords:Generative Artificial Intelligence, Technology Acceptance Model, Socio-technical systems, IT service firms, employee productivity, efficiency, digital transformation.
Generative AI has brought about a new way through which growth is achieved. With the help of software development that has been enhanced using AI, document creation that has been done automatically, intelligent coding, and knowledge management tools, employees are able to do repetitive tasks and those that require a lot of knowledge. In doing this, organizations are now able to achieve better performance through increasing the efficiency of their current employees instead of having growth through expanding the workforce.
1. INTRODUCTION 1.1 Background Introduction of Artificial Intelligence (AI) in the field of digital transformation has been a key driver of success for businesses to automate processes, aid decision-making, and increase efficiency. GenAI refers to the latest developments in the AI domain with regard to Large Language Models (LLMs) developed recently. As opposed to the traditional AI systems that could only execute tasks assigned by humans, GenAI can create software programs, technical documentation, analytics reports, and respond in the form of natural language.
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Even with these advantages, organizations that employ such AI technologies have had varying experiences. Some have made tangible gains in efficiency and effectiveness; however, there have been some cases where there is no proper adoption, inconsistent use, and lack of clear value
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