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Adoption of Generative Artificial Intelligence in Russian Companies: Social Process and Social Implications

Student: Egor Kibalko

Supervisor: Andrey Shevchuk

Faculty: Faculty of Social Sciences

Educational Programme: Sociology (Bachelor)

Final Grade: 8

Year of Graduation: 2024

The purpose of this study is to analyze the social process of implementing generative AI in business, as well as to identify the social consequences of the implementation of generative models for employees and companies. The work examines the strategies of generative AI implementation in Russian companies, analyzes social interaction during technology implementation, and assesses the social changes caused by the integration of generative AI. The research is based on qualitative methodology, including in-depth semi-structured interviews with employees of companies from various industries. A coding procedure and grounded theory method are used to analyze the data in order to identify common trends, challenges, and social implications of the implementation of generative AI in business. The results of the study provide a better understanding of the impact of the implementation of generative AI on social processes in organizations, as well as identify various aspects that characterize the success of this process. The findings can be used to develop recommendations for optimizing the implementation of generative AI in business processes, taking into account social aspects.

Full text (added May 30, 2024)

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