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Shifting accountability to artificial intelligence: delegating challenging decisions to AI for responsibility avoidance

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Listed:
  • Xu, Liying
  • Tian, Huanmeng
  • Zhang, Yuyan
  • Yu, Feng

Abstract

The integration of artificial intelligence (AI) into workplace decisions has led to a growing tendency to delegate decision authority to AI systems. While prior research views this trend as an instrumental means to enhance decision quality, we propose that in no-win dilemmas—where all options entail inevitable loss—individuals strategically turn to AI to offload responsibility. Across eight experiments, we provide robust evidence that responsibility avoidance drives AI delegation in difficult, no-win decisions. This effect is strongest when AI is perceived as both agentic and emotionally detached and is further amplified in socially consequential contexts, such as decisions affecting others or are publicly observable choices. Our research advances the ongoing algorithm aversion versus appreciation debate by demonstrating that AI is appreciated not for its intelligence per se. Rather, its agentic yet emotionless profile fulfills users’ psychological need to offload responsibility in difficult decisions.

Suggested Citation

  • Xu, Liying & Tian, Huanmeng & Zhang, Yuyan & Yu, Feng, 2026. "Shifting accountability to artificial intelligence: delegating challenging decisions to AI for responsibility avoidance," Journal of Business Research, Elsevier, vol. 215(C).
    • Handle: RePEc:eee:jbrese:v:215:y:2026:i:c:s0148296326003486
    DOI: 10.1016/j.jbusres.2026.116313
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