--- title: "Friend or Foe? Teaming Between Artificial Intelligence and Workers with Variation in Experience · AI Fault Line" url: https://aifaultline.com/research/p/doi-10-1287-mnsc-2021-00588/ description: "AI Fault Line is a neutral, evidence-cited field guide to why experts looking at the same developments disagree about AI's effect on productivity, jobs, inequality, regulation and the pace of change." --- [Research](https://aifaultline.com/research/) # Friend or Foe? Teaming Between Artificial Intelligence and Workers with Variation in Experience Weiguang Wang, Guodong Gordon Gao, Ritu Agarwal · Management Science · 11 Oct 2023 [Read original source](https://doi.org/10.1287/mnsc.2021.00588) Where this sits in the debate - [Will AI actually boost productivity and growth?](https://aifaultline.com/debate/productivity/) · its finding: it depends ([why studies differ](https://aifaultline.com/debate/productivity/#why)) Direction of the finding as read from the abstract by an AI model ([AI-written](https://aifaultline.com/about/)). ## Abstract As artificial intelligence (AI) applications become more pervasive, it is critical to understand how knowledge workers with different levels and types of experience can team with AI for productivity gains. We focus on the influence of two major types of human work experience (narrow experience based on the specific task volume and broad experience based on seniority) on the human-AI team dynamics. We developed an AI solution for medical chart coding in a publicly traded company and conducted a field study among the knowledge workers. Based on a detailed analysis performed at the medical chart level, we find evidence that AI benefits workers with greater task-based experience, but senior workers gain less from AI than their junior colleagues. Further investigation reveals that the relatively lower productivity lift from AI is not a result of seniority per se but lower trust in AI, likely triggered by the senior workers’ broader job responsibilities. This study provides new empirical insights into the differential roles of worker experience in the collaborative dynamics between AI and knowledge workers, which have important societal and business implications. This paper was accepted by Kartik Hosanagar, information systems. Funding: This work was supported by Inovalon [Sponsor of the Health Insights AI Laboratory]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2021.00588 . ## About this publication **Leading field journal.** A leading journal in economics or a neighbouring field (on the Tinbergen Institute’s A list or near the top of the RePEc ranking), or a top-rated computer-science venue. Placed by: Leading field journal. [How sources are ranked](https://aifaultline.com/about/#source-ranking). Published 2023 (37 months ago) Citations 115 (OpenAlex) ## Citations in context [Chart: 115 citations, cohort median 397.5] 115 citations — 38th percentile among the 8 indexed papers from 2023 in this collection. Citation counts favor older papers; this compares only same-year papers here, not the whole literature. [Chart: published 2023] □ added to this collection in 2026. author affiliation matches seed institution johns hopkins university — part of why this paper is in the collection. ## More on this topic Related by theme, not necessarily by method or conclusion. - [The Effects of Generative AI on High Skilled Work: Evidence from Three Field Experiments with Software Developers](https://aifaultline.com/research/p/doi-10-2139-ssrn-4945566/) SSRN · 2024 - [GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models](https://aifaultline.com/research/p/doi-10-48550-arxiv-2303-10130/) arXiv · 2023 - [Extending “GPTs Are GPTs” to Firms](https://aifaultline.com/research/p/doi-10-1257-pandp-20251045/) AEA Papers and Proceedings · 2025 - [New Frontiers: The Origins and Content of New Work, 1940–2018](https://aifaultline.com/research/p/doi-10-1093-qje-qjae008/) The Quarterly Journal of Economics · 2024 Overview assembled automatically from collected metadata. [How this site is built](https://aifaultline.com/about/).