Back to Papers

When and How Artificial Intelligence Augments Employee Creativity

Nan Jia, Xueming Luo, Fang Zheng, Chengcheng LiaoManagement创新管理UTD24
Academy of Management Journal2023-03-28Southern California University for Professional Studies; University of Southern California; Temple College; Temple University; Sichuan UniversityDOI
Citations530
Influential12
Semantic Scholar

Can artificial intelligence (AI) assist human employees in increasing employee creativity? Drawing on research on AI–human collaboration, job design, and employee creativity, we examine AI assistance in the form of a sequential division of labor within organizations: in a task, AI handles the initial portion, which is well-codified and repetitive, and employees focus on the subsequent portion, involving higher-level problem-solving. First, we provide causal evidence from a field experiment conducted at a telemarketing company. We find that AI assistance in generating sales leads, on average, increases employees’ creativity in answering customers’ questions during subsequent sales persuasion. Enhanced creativity leads to increased sales. However, this effect is much more pronounced for higher-skilled employees. Next, we conducted a qualitative study using semi-structured interviews with the employees. We found that AI assistance changes job design by intensifying employees’ interactions with more serious customers. This change enables higher-skilled employees to generate innovative scripts and develop positive emotions at work, which are conducive to creativity. By contrast, with AI assistance, lower-skilled employees make limited improvements to scripts and experience negative emotions at work. We conclude that employees can achieve AI-augmented creativity, but this desirable outcome is skill-biased by favoring experts with greater job skills.

CreativityPsychologyScripting languagePersuasionTask (project management)Applied psychologyKnowledge managementMarketingSocial psychologyBusinessManagementComputer science
Related Papers (8-Dimension Scoring)

Gaining Legitimacy by Being Different: Optimal Distinctiveness in Crowdfunding Platforms

Karl Taeuscher, Ricarda B. Bouncken, Robin Pesch · Academy of Management Journal

Score: 64

When Conscientious Employees Meet Intelligent Machines: An Integrative Approach Inspired by Complementarity Theory and Role Theory

Pok Man Tang, Joel Koopman, Shawn T. McClean, Jack H. Zhang, Chi Hon Li, David De Cremer, Yizhen Lu, Chin Tung Stewart Ng · Academy of Management Journal

Score: 64

Networks, Creativity, and Time: Staying Creative through Brokerage and Network Rejuvenation

Giuseppe Soda, Pier Vittorio Mannucci, Ronald S. Burt · Academy of Management Journal

Score: 64

Paradoxical Leadership and Innovation in Work Teams: The Multilevel Mediating Role of Ambidexterity and Leader Vision as a Boundary Condition

Melody J. Zhang, Yan Zhang, Kenneth S. Law · Academy of Management Journal

Score: 64

Minimal and Adaptive Coordination: How Hackathons’ Projects Accelerate Innovation without Killing it

Hila Lifshitz‐Assaf, Sarah Lebovitz, Lior Zalmanson · Academy of Management Journal

Score: 64

Artificial Intelligence Coaches for Sales Agents: Caveats and Solutions

Xueming Luo, Marco Shaojun Qin, Zheng Fang, Zhe Qu · Journal of Marketing

Score: 56

Augmenting Medical Diagnosis Decisions? An Investigation into Physicians’ Decision-Making Process with Artificial Intelligence

Ekaterina Jussupow, Kai Spohrer, Armin Heinzl, Joshua Gawlitza · Information Systems Research

Score: 51

Recognizing and Utilizing Novel Research Opportunities with Artificial Intelligence

Georg von Krogh, Quinetta M. Roberson, Marc Gruber · Academy of Management Journal

Score: 50