About

Matt Beane is an Associate Professor at the University of California, Santa Barbara, where he studies how skill is built in work involving intelligent machines such as AI and robotics. His research has been published in top management outlets including Administrative Science Quarterly, Organization Science, and Harvard Business Review, as well as technical outlets like CHI and HRI. Beane is the author of the book The Skill Code: How to Save Human Ability in an Age of Intelligent Machines, published by HarperCollins. He is also the co-founder and CEO of SkillBench, a platform that converts AI usage data into actionable insights to help CTOs steer technological transformation and enable software developers to grow. Recognized as a Human-Robot Interaction Pioneer in 2012 and named to the Thinkers50 Radar list in 2021, Beane is a Digital Fellow with the Stanford Digital Economy Lab and MIT’s Initiative on the Digital Economy. His work focuses on understanding how organizations and individuals develop and preserve skills in the context of advancing intelligent technologies.

Research topics

• Computer science
• Knowledge management
• Human–computer interaction
• Sociology
• Artificial intelligence

Selected publications

• Developmental Uncertainty: When Coordination Demands Enable Occupational Mobility Across Status Boundaries

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Learning to Automate: How Multi-Site Firms Distribute Exploration and Exploitation Across Facilities

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Not for the Money: How Performance Incentives Create Signaling Channels for Career-Oriented Workers

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Solve and Be Seen: How Workers in Deskilled Jobs Build Complex Skill as New Automation Arrives

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Precision Proactivity: Measuring Cognitive Load in Real-World AI-Assisted Work

  ArXiv.org · 2025-05-15

  preprintOpen accessSenior author

  Systems like ChatGPT and Claude assist billions through proactive dialogue-offering unsolicited, task-relevant information. Drawing on Cognitive Load Theory, we study how cognitive load shapes performance in AI-assisted knowledge work. We recruited 34 financial professionals to complete a complex valuation task using GPT-4o and developed a transcript-based framework estimating intrinsic and extraneous load from computational indicators anchored in a task decomposition and knowledge graph. Across 1,178 participant-subtask observations, AI-generated content usage is positively associated with quality, while extraneous load shows the largest negative association-roughly three times that of intrinsic load. Mediation reveals a compensatory pathway partially offsetting but not eliminating load-related deficits. Extraneous load persists within speakers and spills asymmetrically to model responses. Model-initiated task switching is the strongest predictor of decline. Expertise moderates these dynamics: less experienced professionals face larger penalties and derive greater marginal gains from AI-generated content, yet are not those who most increase uptake under load.

  PublisherOA PDFDOI

• Hatim A. Rahman. Inside the Invisible Cage: How Algorithms Control Workers RahmanHatim A.Inside the Invisible Cage: How Algorithms Control Workers. University of California Press, 2024. 288 pp. $29.95, paper.

  Administrative Science Quarterly · 2025-07-31

  article1st authorCorresponding
  PublisherDOI

• Minds and Machines: Expertise in an Age of Intelligent Machines

  Academy of Management Proceedings · 2024-07-09

  articleSenior author

  Intelligent machines are transforming the nature of knowledge, skills, and expertise, challenging many of our assumptions about work and organizing. Researchers have long emphasized the impact of emerging technologies on reshaping interactions within organizations and occupational communities. From paper mill operators with software systems (Zuboff, 1988), radiologists with computerized CT scanners (Barley, 1986), librarians with internet search (Nelson & Irwin, 2014), and NASA scientists with open-source innovation (Lifshitz- Assaf, 2018) scholars have found that the introduction of digital technologies can occasion changes to occupational identities and trouble the boundaries of domain knowledge within and between organizations. However, our understanding of expertise in the era of machine learning, algorithms, and AI is still nascent. Unlike previous digital technologies, intelligent machine applications can handle complex decision-making tasks and analysis of large amounts of structured and unstructured data, disintermediating the tasks of managers and workers (Kellogg et al., 2020; Murray et al., 2021; Faraj et al., 2018). As such, recent calls for research emphasize the need for more theorizing on expertise and more empirical studies on how workers, occupational communities, and organizations can adapt to and cultivate the skills needed in this new world of work (Heimstädt et al., 2023; Nicolini et al., 2022). Therefore, this symposium provides new perspectives and insights at the nexus of intelligent machines and the evolving nature of knowledge, skills, and expertise. It will consist of two conceptual and three empirical papers that grapple with differing forms of intelligent technologies and their impacts. In concert, these presentations foreground and question the assumptions and heuristics that scholars of work, management, and organizing have traditionally held preceding the proliferation of intelligent machines. This symposium is designed to encourage discussion and integrate diverse theoretical and methodological approaches to the evolving landscape of work and technology. How Autographic Affiliations Shape Patterns Of Technology Use Author: Callen Anthony; New York U. Ethical Expertise in the Era of Fair Algorithms in Organizations Author: Sarah Lebovitz; U. of Virginia Author: Emmanouil Gkeredakis; IESE Business School Monsters of Our Own Creation: AI, Occupational Cannibalization, and the Future of Work Author: Kevin Woojin Lee; U. of British Columbia Integrated Organizational Training in the Age of Artificial Intelligence Author: Hatim A. Rahman; Northwestern Kellogg School of Management Characteristics as a Complement to Process: Theorizing Skill in an Age of Intelligent Machines Author: Matt Beane; U. of California, Santa Barbara

  PublisherDOI

• Designing Technology that Preserves Skill Development

  Research-Technology Management · 2024-11-01 · 2 citations

  articleSenior author
  PublisherDOI

• Haunted Adoption: How Applied Experts Can Drive Organizations to Incorporate Technology without Strong Managerial Support

  SSRN Electronic Journal · 2024-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Inverted Apprenticeship: How Senior Occupational Members Develop Practical Expertise and Preserve Their Position When New Technologies Arrive

  Organization Science · 2023-08-07 · 29 citations

  article1st authorCorresponding

  New technologies create a dilemma for senior members of occupations. Traditionally, practical expertise and position are considered correlates, yet when new technologies arrive, they may be knocked out of alignment. This means that senior members must develop new expertise lest their position be threatened. However, because position often signifies expertise, developing new practical expertise may be challenging. Indeed, senior members face strong pressures not to appear to nor actually devote time to comprehensive formal training as they are booked with complex problems using prior methods, they are responsible for the learning of junior members, and they have passed early career training windows. Through comparative ethnographic field studies of urological surgery and investment banking, we show that “inverted apprenticeships,” defined as configured struggle and restructured interactions with junior members that allow senior members to develop practical expertise with new technologies while maintaining their position, resolve this dilemma. We identify four pathways that senior experts took to structure these inverted apprenticeships, including seeking, stalling, leveraging, and confronting. We uncover the conditions of each pathway and trace their consequences. Although these pathways allowed senior members to enhance or preserve their position, they generated widely varying practical expertise with the new technology. Furthermore, the majority of these pathways undermined the learning of those most junior, who were supposed to be developing expertise through their interactions with seniors. Funding: This work was supported by the Strategic Management Society [Grant SRF-2015DP-0063] and the Social Science and Humanities Research Council of Canada [Grant 752-2014-0378].

  PublisherDOI

Frequent coauthors

• Wanda J. Orlikowski

  4 shared

• Kevin Woojin Lee

  4 shared

• Solace Shen

  3 shared

• Henny Admoni

  Carnegie Mellon University

  2 shared

• Astrid M. Rosenthal‐von der Pütten

  RWTH Aachen University

  2 shared

• Callen Anthony

  2 shared

• Matt Marge

  Carnegie Mellon University

  2 shared

• Daniel A. Lazewatsky

  2 shared

Education

• Ph.D., Sloan School of Management

  Massachusetts Institute of Technology

  2017

• MSMS, Information Technologies

  Massachusetts Institute of Technology

  2014

Awards & honors

• Human-Robot Interaction Pioneer (2012)
• Thinkers50 Radar list (2021)