Do Early Career Researchers Consider <scp>AI</scp> as an Opportunity or a Threat? A Pathfinding Study

ABSTRACT The article presents the latest (2025) iteration of the Harbingers longitudinal project on early career researchers (ECRs), artificial intelligence (AI) and scholarly communications. In conversation with a purposive and diverse sample of more than 60 ECRs in six countries and numerous subjects, we present an evaluation of a pressing issue: what impact will AI have on their work and career? An important issue is that widespread media speculation suggests that it is entry‐level positions that will be hit hardest by AI. While ECRs were asked 50 plus questions during interviews, none were directly asked about changes to job security and employment prospects, yet much of relevance was volunteered in answering related AI questions. Adding a new methodological dimension to the Harbingers project, we employed AI (NotebookLM) for an initial qualitative analysis of the interview data, with findings reviewed and corrected by the national interviewers. We conclude that AI is a double‐edged sword which has huge potential as well as posing significant challenges. The AI‐assisted analysis proved effective at identifying broad themes, though human oversight was essential to capture nuance, differences between cohorts, and unusual cases. Finally, given that we were working with a select and relatively small sample to inform a larger study, the data should be seen as illuminating and filling a research lacuna, rather than a definitive result in a fast‐changing field.

Authors

Institutions

Publication Details

Journal
Learned Publishing
Published
2026-05-12
DOI
https://doi.org/10.1002/leap.2068
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Do Early Career Researchers Consider AI as an Opportunity or a Threat? A Pathfinding Study

Abdullah Abrizah, Eti Herman, Tatyana Polezhaeva, Jorge Revez et al.
Learned Publishing
Computational and Text Analysis Methods
article

Do Early Career Researchers Consider AI as an Opportunity or a Threat? A Pathfinding Study

Abdullah Abrizah, Eti Herman, Tatyana Polezhaeva, Jorge Revez, John Akeroyd, David Nicholas, Anne Gere, Marzena Swigon, Blanca Rodríguez‐Bravo, David Clark
article en

Abstract

ABSTRACT The article presents the latest (2025) iteration of the Harbingers longitudinal project on early career researchers (ECRs), artificial intelligence (AI) and scholarly communications. In conversation with a purposive and diverse sample of more than 60 ECRs in six countries and numerous subjects, we present an evaluation of a pressing issue: what impact will AI have on their work and career? An important issue is that widespread media speculation suggests that it is entry‐level positions that will be hit hardest by AI. While ECRs were asked 50 plus questions during interviews, none were directly asked about changes to job security and employment prospects, yet much of relevance was volunteered in answering related AI questions. Adding a new methodological dimension to the Harbingers project, we employed AI (NotebookLM) for an initial qualitative analysis of the interview data, with findings reviewed and corrected by the national interviewers. We conclude that AI is a double‐edged sword which has huge potential as well as posing significant challenges. The AI‐assisted analysis proved effective at identifying broad themes, though human oversight was essential to capture nuance, differences between cohorts, and unusual cases. Finally, given that we were working with a select and relatively small sample to inform a larger study, the data should be seen as illuminating and filling a research lacuna, rather than a definitive result in a fast‐changing field.

Learned PublishingVol. 39(3)
University of Lisbon (PT), National Research Tomsk State University (RU), University of Michigan (US), Berkshire College of Agriculture (GB), University of Malaya (MY), Michigan United (US), Uniwersytecki Szpital Kliniczny w Olsztynie (PL), Universidad de León (ES)
Decent work and economic growth
Openalex Percentile: Top 3%
Computational and Text Analysis Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.