The inevitability of AI: a study of undergraduate students’ perceptions of AI tools in their future careers

Introduction. Artificial intelligence (AI) tools garner more attention every day, questions have arisen regarding their possible negative impacts in future job markets. Some predict a potential for massive job losses, especially in high-skilled jobs. This study seeks to explore undergraduate students’ perceptions of how these tools might affect their future careers. Method. This study follows a case study design, employing phenomenological interviews as a research method. The data set was made up of interviews with 17 undergraduate students. Analysis. Data were analysed by employing constant comparative analysis, with various rounds of coding including the creation of open, axial, and structural codes. Results. Students saw AI tools as an inevitable part of their future work. Participants expressed their intention to learn how to optimize their use of various tools, which they see as having the potential to positively benefit them in their future careers. They do not perceive AI to be a viable substitute for their skills, especially in terms of identifying misinformation and emotions. Conclusions. Academic institutions must provide curricular spaces which allow students to harness the power of AI tools. While employers should also make efforts to train employees to make the most of AI tools.

Authors

Institutions

Publication Details

Journal
Information Research an international electronic journal
Published
2025-03-11
DOI
https://doi.org/10.47989/ir30iconf47308
Citations
1
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
2.37
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The inevitability of AI: a study of undergraduate students’ perceptions of AI tools in their future careers

Mónica Colón‐Aguirre, Kawanna Bright
1 citations
Information Research an international electronic journal
Ethics and Social Impacts of AI
2.37
article

The inevitability of AI: a study of undergraduate students’ perceptions of AI tools in their future careers

Mónica Colón‐Aguirre, Kawanna Bright
article en
1 citations

Abstract

Introduction. Artificial intelligence (AI) tools garner more attention every day, questions have arisen regarding their possible negative impacts in future job markets. Some predict a potential for massive job losses, especially in high-skilled jobs. This study seeks to explore undergraduate students’ perceptions of how these tools might affect their future careers. Method. This study follows a case study design, employing phenomenological interviews as a research method. The data set was made up of interviews with 17 undergraduate students. Analysis. Data were analysed by employing constant comparative analysis, with various rounds of coding including the creation of open, axial, and structural codes. Results. Students saw AI tools as an inevitable part of their future work. Participants expressed their intention to learn how to optimize their use of various tools, which they see as having the potential to positively benefit them in their future careers. They do not perceive AI to be a viable substitute for their skills, especially in terms of identifying misinformation and emotions. Conclusions. Academic institutions must provide curricular spaces which allow students to harness the power of AI tools. While employers should also make efforts to train employees to make the most of AI tools.

Information Research an international electronic journalVol. 30(iConf)
University of South Carolina (US), East Carolina University (US)
Openalex Percentile: Top 14%
Ethics and Social Impacts of AI
2.37
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.