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This study introduces an AI chatbot using Retrieval-Augmented Generation (RAG) to improve new employee onboarding. The RAG chatbot enhances employee satisfaction and retention, showing AI

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Area of Science:

  • Human-Computer Interaction
  • Artificial Intelligence in Human Resources
  • Organizational Psychology

Background:

  • Effective employee integration is vital for job satisfaction and retaining staff.
  • Traditional onboarding processes often face challenges in providing personalized and timely support.
  • The need for innovative solutions to enhance the new hire experience is growing.

Purpose of the Study:

  • To present a novel chatbot system for optimizing the employee onboarding process.
  • To leverage Retrieval-Augmented Generation (RAG) for interactive and personalized onboarding assistance.
  • To evaluate the chatbot's impact on employee satisfaction and retention.

Main Methods:

  • Development of a chatbot utilizing Retrieval-Augmented Generation (RAG) architecture.
  • Implementation of the chatbot to provide support during the employee integration phase.
  • Assessment of user interaction and feedback to gauge effectiveness.

Main Results:

  • The RAG-powered chatbot demonstrated promising results in addressing onboarding challenges.
  • Interactive and personalized support led to positive indicators of employee satisfaction.
  • The system showed potential for improving overall staff retention.

Conclusions:

  • AI-assisted solutions, specifically chatbots with RAG, can significantly enhance onboarding efficiency.
  • This approach offers a scalable method to boost employee satisfaction and retention.
  • Potential for broader applications of this AI-driven onboarding strategy in sectors like healthcare.