关键词: 极限目标, 人工智能, 人-AI合作, 创造力

Abstract: As artificial intelligence (AI) is adopted and deployed in enterprises, an increasing number of teams are moving away from traditional goal-setting methods and, in AI-enabled contexts, using stretch goals to spark employee and team creativity. However, the emergence of such goals in AI-enabled settings and their effects on creativity remain underexplored and empirically untested. Accordingly, this study focuses on: (1) uncovering how stretch goals emerge in AI-enabled settings; (2) drawing on socio-technical systems theory to examine the mediating role of individual exploratory learning between stretch goals and individual creativity, and the moderating role of perceived AI usefulness; (3) drawing on socio-technical systems theory to test the mediating role of human-AI collaboration between stretch goals and team creativity, and the moderating role of human-AI role clarity; (4) application verification of the formation mechanism and impact effects of stretch goals. The core conclusions of the “environmental stimuli → goal setting → employee behavioral outcomes” framework derived from the aforementioned research are applied to practical scenarios, so as to provide a reference for enterprises to enhance the creativity of individuals and teams. The findings aim to fill the research gap on stretch goals in AI-enabled contexts and to guide managers in leveraging AI to overcome constraints associated with stretch goals.

Key words: Key Words: Stretch Goal, Artificial Intelligence, Human-AI cooperation, Creativity