# How does organizational AI adoption affect employees’ job crafting behaviors? An approach-avoidance perspective

## TL;DR

This paper explores how adopting AI in organizations affects employees' job crafting behaviors through approach and avoidance motivations.

## Contribution

It introduces an approach-avoidance framework to explain how AI adoption influences job crafting behaviors.

## Key findings

- AI-supported autonomy mediates the positive link between AI adoption and approach job crafting.
- AI anxiety mediates the positive link between AI adoption and avoidance job crafting.
- AI knowledge sharing moderates the effects of AI adoption on motivational reactions and job crafting.

## Abstract

Artificial intelligence (AI) technology has significantly changed human work. Increasingly, organizations are promoting the integration of AI into employees’ work processes. While existing research has explored AI applications in the workplace, relatively little attention has been devoted to understanding how organizational AI adoption influences employees’ motivational reactions and the subsequent impacts. Drawing on approach-avoidance motivational theory, this research explores the fundamental mechanisms through which organizational AI adoption influences employees’ approach and avoidance job crafting behaviors.

A three-wave survey was conducted among 650 employees from five enterprises that actively utilize AI tools in China, yielding 487 valid responses. Data were analyzed using SPSS 21.0 and Mplus 7.0 to test the proposed hypotheses.

The findings suggest that organizational AI adoption influences employees’ approach or avoidance motivation, which in turn shapes their job crafting behaviors. Specifically, AI-supported autonomy mediates the positive relationship between organizational AI adoption and approach job crafting. Conversely, AI anxiety mediates the positive relationship between organizational AI adoption and avoidance job crafting. Furthermore, AI knowledge sharing moderates the effects of organizational AI adoption on motivational reactions and the indirect effects of organizational AI adoption on approach and avoidance job crafting, respectively.

This study introduces the approach-avoidance perspective, providing a valuable framework for understanding employees’ motivational responses and job crafting behaviors following the organizational AI adoption, thereby expanding the application scope of the approach-avoidance motivational theory. Organizations should leverage the role of AI in knowledge sharing to enhance employees’ approach motivation and reduce their avoidance motivation. Future research may focus on developing an AI-specific job crafting construct and exploring additional antecedents of AI-related crafting behaviors.