March 26, 2024 | 12:00 pm - 12:30 pm ET 


MSI Webinar: How and When Artificial Intelligence Augments Employee Creativity

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 skillbiased by favoring experts with greater job skills.


Watch the Recording

Download the Presentation

Read the Summary


Xueming Luo

Temple University

Xueming Luo is the Charles Gilliland Distinguished Chair Professor of Marketing, Professor of Strategy and MIS, and Founder/ Director of the Global Institute for Artificial Intelligence & Business Analytics in the Fox School of Business at Temple University. His research is quantitative in nature and focuses on integrating artificial intelligence technologies, big data machine learning, econometrical methods, and field experiments to model, explain, and optimize customer experience, company strategies, platform designs, and creator & sharing economy. He is an interdisciplinary thought-leader in leveraging AI/ML algorithms, text/audio/image/video data, and causality inference for digital marketing, mobile targeting, social media analytics, brand activism, and social responsibility. Xueming has worked with leading global companies in mobile communications, banking, e-commerce, health care, education, pharmaceutical, and petroleum industries. His research has been featured by premier journals in Marketing (MkSc, JM, and JMR), Management and Strategy (MgSc, SMJ, AMJ, and POM), and Information Systems (ISR and MISQ). He has been ranked as top 8th worldwide regarding Author Productivity in the Premier Marketing Journals (JCR, JM, JMR, MKSC) during 2013-2022. Xueming has over 24,700 citations on Google Scholar.

By using you agree to our use of cookies as identifiers and for other features of the site as described in our Privacy Policy.