Paper Number

ICIS2025-2006

Paper Type

Complete

Abstract

This study examines how different AI assistance modalities, such as conversational AI and search-based systems, influence motivational dynamics in knowledge work. Using expectancy theory, we identify three key findings: (1) AI assistance shifts the primary motivational driver from self-efficacy to outcome valuation; (2) conversational AI induces a unique compensatory effort reduction effect where users with higher self-efficacy strategically reduce effort through AI delegation; and (3) conversational AI strengthens the indirect pathway from motivation to performance through strategic effort allocation. Our collaboration expectancy model integrates motivational and technological perspectives, extending both expectancy theory and human-AI collaboration frameworks. The findings contribute to our understanding of how AI transforms fundamental psychological mechanisms in task performance and have implications for the organizational implementation of AI technologies. This suggests that different assistance modalities require distinct management approaches that recognize the emerging collaborative dynamics between humans and AI systems.

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Dec 14th, 12:00 AM

AI-Assisted Task Performance: The Moderating Role of Assistance Modality on Motivational Dynamics

This study examines how different AI assistance modalities, such as conversational AI and search-based systems, influence motivational dynamics in knowledge work. Using expectancy theory, we identify three key findings: (1) AI assistance shifts the primary motivational driver from self-efficacy to outcome valuation; (2) conversational AI induces a unique compensatory effort reduction effect where users with higher self-efficacy strategically reduce effort through AI delegation; and (3) conversational AI strengthens the indirect pathway from motivation to performance through strategic effort allocation. Our collaboration expectancy model integrates motivational and technological perspectives, extending both expectancy theory and human-AI collaboration frameworks. The findings contribute to our understanding of how AI transforms fundamental psychological mechanisms in task performance and have implications for the organizational implementation of AI technologies. This suggests that different assistance modalities require distinct management approaches that recognize the emerging collaborative dynamics between humans and AI systems.

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