TY - GEN
T1 - Career Advisory with Artificial Intelligence
AU - Ade-Ibijola, Abejide
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - Finding a job is becoming more difficult in the current day. This is due to the advancements in artificial intelligence (AI) and trends in the jobs that can be automated, or tasks that are doable by machines. If AI has a say in job displacement, we could also use it in the prediction of future jobs. This is an important exercise for young Africans studying in higher education institutions. In this paper, we have proposed an AI-powered career advisory system that uses real-time job market data, skills mapping, and predictive analytics to offer personalised guidance to students about jobs that are going extinct, relevant skills that will be relevant, and future prospects. This work employs design science research methodology, integrating user selection with AI algorithms to dynamically recommend career paths. Our evaluation by students highlights a 72% approval of their trust in the system, a 64% likelihood of recommendation to other users, and improved alignment of user skills with future job opportunities. The system shows significant potential to improve the readiness of the workforce and bridge the gaps between education and employment. This AI-driven approach can redefine career advisory systems, allowing students to adapt to the evolving job market and mitigate the risks of unemployment.
AB - Finding a job is becoming more difficult in the current day. This is due to the advancements in artificial intelligence (AI) and trends in the jobs that can be automated, or tasks that are doable by machines. If AI has a say in job displacement, we could also use it in the prediction of future jobs. This is an important exercise for young Africans studying in higher education institutions. In this paper, we have proposed an AI-powered career advisory system that uses real-time job market data, skills mapping, and predictive analytics to offer personalised guidance to students about jobs that are going extinct, relevant skills that will be relevant, and future prospects. This work employs design science research methodology, integrating user selection with AI algorithms to dynamically recommend career paths. Our evaluation by students highlights a 72% approval of their trust in the system, a 64% likelihood of recommendation to other users, and improved alignment of user skills with future job opportunities. The system shows significant potential to improve the readiness of the workforce and bridge the gaps between education and employment. This AI-driven approach can redefine career advisory systems, allowing students to adapt to the evolving job market and mitigate the risks of unemployment.
KW - AI career advisory
KW - AI in career counseling
KW - career guidance
KW - job recommendations
KW - skill integration
UR - https://www.scopus.com/pages/publications/105028902258
U2 - 10.1007/978-3-032-14706-6_21
DO - 10.1007/978-3-032-14706-6_21
M3 - Conference contribution
AN - SCOPUS:105028902258
SN - 9783032147059
T3 - Communications in Computer and Information Science
SP - 264
EP - 279
BT - Artificial Intelligence and Knowledge Processing - 5th International Conference, Proceedings
A2 - Kannan, Hemachandran
A2 - Villamarin Rodriguez, Raul
A2 - Rege, Manjeet
A2 - Piuri, Vincenzo
A2 - AdeIbijola, Abejide
A2 - López González de León, Miguel
A2 - Ben Dhaou, Imed
PB - Springer Science and Business Media Deutschland GmbH
T2 - 5th International Conference on Artificial Intelligence and Knowledge Processing, AIKP 2025
Y2 - 23 October 2025 through 25 October 2025
ER -