Impact of Gen AI on Employees within High-Tech Organisations

Relevance: Artificial intelligence (AI) technologies have undergone substantial transformations driven by technological advancements, with Generative artificial intelligence (Gen AI) innovation appearing as a vital tool to augment human capability. Despite the rapid adoption of these technologies, there is still limited research demonstrating their effects, particularly on employees at High-Tech organisations. Thus, connecting the gap between domain experience and theoretical frameworks is necessary to understand the Impact of Gen AI adoption. Purpose: The research aims to explore how Gen AI impacts employees within High-Tech organisations, focusing on how work processes, roles, tasks, and skills evolve. It also addresses the governance and ethical challenges associated with Gen AI adoption. The research aims to address the gap between theoretical understanding and practical adoption, extending the sociotechnical system theory and providing actionable insights. Method: The research approach is qualitative, exploratory, and abductive approach. Data was collected from 9 semi-structured interviews, 7 of which are from the case studie. Interviews were conducted through teams and Webex software, focusing on Gen AI's impact on employees' roles, tasks, and skills, and the adoption method, with their perspectives toward the adoption. The research focused on how employees should adapt Gen AI in organisations through the lens of STS theory. Result: the findings of this research indicate that employees within High-tech organisations often adopt Gen AI in an informal, bottom-up method, driven by employees voluntarily rather than formal structures. This method of adoption leads to inconsistency in knowledge disparities, while it supports creativity and innovation. Further, challenges arise within Gen AI ethical use and data privacy, underscoring the necessity of human collaboration and oversight to ensure reliability. Thereafter, organisations must promote open cultures to balance between innovation and transparent governance of Gen AI adoption.