Location
Hilton Waikoloa Village, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
7-1-2025 12:00 AM
End Date
10-1-2025 12:00 AM
Description
The rapid advancements of artificial intelligence (AI) have led to its widespread adoption in enhancing productivity across various domains, including both personal productivity and workplace efficiency. Despite these advancements, the effective onboarding of novices, particularly in complex environments with extensive documentation, remains a significant challenge. Therefore, this paper explores the design of AI assistants to support novices. Utilizing a design science research approach, we collaborate with a leading pharmaceutical manufacturer to develop and evaluate an AI assistant to support novices during their onboarding. Grounded in scaffolding theory, we identify two design requirements and propose three design principles: Metadata Filtering, Graduated Complexity, and Sequential Query Generation. The evaluation of these principles demonstrates the AI assistant's effectiveness in generating accurate and contextually relevant responses, facilitating the onboarding of novices. This study provides valuable insights into the design of AI assistants, contributing to the theoretical understanding of AI-driven scaffolding and practical applications in complex industrial settings.
Recommended Citation
Holstein, Joshua; Müller, Patrick; Vössing, Michael; and Fromm, Hansjoerg, "Designing AI Assistants for Novices: Bridging Knowledge Gaps in Onboarding" (2025). Hawaii International Conference on System Sciences 2025 (HICSS-58). 2.
https://aisel.aisnet.org/hicss-58/in/ai_based_assistants/2
Designing AI Assistants for Novices: Bridging Knowledge Gaps in Onboarding
Hilton Waikoloa Village, Hawaii
The rapid advancements of artificial intelligence (AI) have led to its widespread adoption in enhancing productivity across various domains, including both personal productivity and workplace efficiency. Despite these advancements, the effective onboarding of novices, particularly in complex environments with extensive documentation, remains a significant challenge. Therefore, this paper explores the design of AI assistants to support novices. Utilizing a design science research approach, we collaborate with a leading pharmaceutical manufacturer to develop and evaluate an AI assistant to support novices during their onboarding. Grounded in scaffolding theory, we identify two design requirements and propose three design principles: Metadata Filtering, Graduated Complexity, and Sequential Query Generation. The evaluation of these principles demonstrates the AI assistant's effectiveness in generating accurate and contextually relevant responses, facilitating the onboarding of novices. This study provides valuable insights into the design of AI assistants, contributing to the theoretical understanding of AI-driven scaffolding and practical applications in complex industrial settings.
https://aisel.aisnet.org/hicss-58/in/ai_based_assistants/2