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Resumo(s)
This thesis explores the integration of Large Language Models (LLMs) in Human Resources to
improve employee feedback processes. It examines challenges in analyzing qualitative
feedback in large organizations and proposes Thrivio, an AI-driven Minimum Viable Product
(MVP), as a solution. The research combines a comprehensive literature review, mixed methods empirical research, and the development and testing of Thrivio. Focusing on enhancing
HR decision-making through AI analytics, the thesis presents a novel bottom-up approach to
employee feedback, culminating in a market strategy and future roadmap for Thrivio, thereby
contributing to the field of impact entrepreneurship and innovation.
Descrição
Palavras-chave
Artifical intelligence Human resources Employer management Feedback Corporate culture Employer engagement Opportunity identification Qualitative research Mvp testing Corporate challenges Iterative development Large language models
