AI-Driven Optimization of Onboarding in Large Organizations: Development of the Prototype 'bAİby'.

Autores/as

  • Tamer Uzun Skilled GmbH
  • Michael Müller Ansbach University of Applied Sciences

Palabras clave:

Generative AI, Onboarding, Knowledge Management, Public Sector, HR Digitalization

Resumen

 Effective onboarding is essential for integrating employees into large organizations, yet challenges like administrative burdens and cultural barriers hinder efficiency and engagement. Within diverse and complex organizations, generative artificial intelligence (AI) offers innovative solutions to enhance onboarding. This study explores AI's potential to personalize and streamline employee integration, across private and public sectors.

The objective is to develop an AI-based prototype that optimizes onboarding in large organizations (>1,000 employees) through task automation, content personalization, and improved employee integration. Additionally, the prototype's applicability to various sectors, including public organizations, will be evaluated.

The approach combines a literature review with qualitative interviews from experts at private enterprises (e.g., BASF, BMW) and a public sector organization (City of Nuremberg). Insights informed the development of prototype 'bAİby' using a generative AI model. The prototype was designed to automate content generation, tailor learning paths, and enhance engagement through gamification and an AI chatbot, with a focus on usability and scalability.

The prototype significantly reduces administrative workload by automating content creation and enhances employee satisfaction through personalized learning paths and gamification. Features like an AI chatbot address information overload and foster social integration, though cultural personalization requires further refinement. The system can be flexibly adapted to various requirements, such as different employee groups and organizational processes.

The prototype demonstrates generative AI's transformative impact on onboarding, balancing efficiency and individualization across sectors. Future research should explore long-term effects on employee retention and broader scalability.

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Publicado

2025-12-05

Cómo citar

Uzun, T., & Müller, M. (2025). AI-Driven Optimization of Onboarding in Large Organizations: Development of the Prototype ’bAİby’. Congreso Internacional De Conocimiento E Innovación - Ciki, 1(1). Recuperado a partir de https://proceeding.ciki.ufsc.br/index.php/ciki/article/view/1667