Measuring GenAI and Productivity in Work and Careers
DETAILS
Call for Papers
Measuring GenAI and Productivity in Work and Careers
Journal: Personnel Review
Publisher: Emerald Publishing
Manuscript Submission Opens: 31 August 2026
Manuscript Submission Deadline: 31 January 2027
Personnel Review invites submissions for a Special Issue examining how Generative Artificial Intelligence (GenAI) is transforming productivity, work practices, human-AI collaboration, HR systems, skills, and career development.
About the Special Issue
Generative AI is rapidly becoming embedded in workplace processes, organizational systems, HR practices, and individual careers. As employees increasingly use AI for task execution, decision-making, and knowledge work, traditional assumptions about how productivity is defined, measured, and compared are becoming more difficult to sustain.
A central focus of this Special Issue is human-AI augmentation, where individuals and AI systems jointly contribute to workplace outputs. Such collaboration raises important questions about how organizations can distinguish human and AI contributions, evaluate performance fairly, and understand productivity when work is jointly produced.
The Special Issue seeks research that moves beyond general questions of GenAI adoption to investigate how work is actually being reconfigured, how productivity should be conceptualized and measured, and what these developments mean for employees, careers, HR practices, and organizations.
Topics of Interest
Submissions may address, but are not limited to:
Conceptualizing productivity in AI-enabled work and careers
Defining and measuring productivity in GenAI contexts
Distinguishing AI exposure, use, and augmentation
Human-AI collaboration in workplace tasks
Measuring human versus AI contributions to outputs
Attribution of individual and AI-assisted performance
GenAI and employee productivity
Changes in the distribution of workplace performance
Effects of GenAI on high and lower performers
GenAI and skill development
AI-related reskilling and capability development
Career trajectories in AI-enabled workplaces
GenAI and employability
HR practices supporting AI-enabled work
Job design and human-AI augmentation
Organizational context and AI-related productivity
Performance management in AI-supported workplaces
Methodological approaches for studying AI and work
Multi-source and behavioural data
Longitudinal research on GenAI and productivity
Research and Methodological Focus
The Special Issue particularly encourages research capable of generating stronger evidence on GenAI's workplace effects, including studies using:
Multi-source data
Longitudinal research designs
Behavioural data
Alternative forms of workplace and performance data
Submission Information
Submission Opens: 31 August 2026
Submission Deadline: 31 January 2027
Manuscripts should be submitted through the Personnel Review ScholarOne Manuscripts platform.
Authors must select “Measuring GenAI and Productivity in Work and Careers” from the Special Issue options during submission.
Submitted manuscripts must follow the journal's author guidelines, be original, and must not have been previously published or be under consideration elsewhere while under review.
Submission Contact: Tony Fang — tfang@mun.ca
Guest Editors
Tony Fang
Email: tfang@mun.ca
Jennifer A. Harrison
Email: jharrison@em-normandie.fr
Fei Song
Email: fsong@torontomu.ca
Mingwei Liu
Email: mingwei@smlr.rutgers.edu
Posted on ServiceSetu Academics — Premier Platform for Academic Opportunities & Research Collaboration.
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