AI-Supported Career Development: Opportunities, Challenges and a Human-Centred Framework for Sustainable Employability

Volume 11, Issue 3, 2026

International Journal of Commerce and Management Studies, ISSN 2456-3684

Paper Title

Author Name and Affiliation

Dr. V. Srividhya

Associate Professor in Commerce, Government First Grade College, Channapatna, Bangalore South District, Karnataka

Email: srividhya0510@gmail.com

Abstract

Purpose. Artificial intelligence (AI) is increasingly embedded in human resource development, learning, talent management and career-support processes. This conceptual article examines how AI can contribute to employee career development and sustainable employability while preserving human agency. Approach. The article integrates recent scholarship published primarily during 2023–2026 with established career and sustainable-employability perspectives. Findings. Recent reviews show that AI can improve career exploration, skills analysis, personalized learning and career management, but can also intensify job insecurity, privacy concerns, perceived unfairness and over-reliance on algorithmic recommendations. Empirical studies further indicate that transparency, data governance, trusted leadership, human involvement and AI literacy are relevant to employee trust and acceptance. Contribution. The article develops a Human-AI Career Development Framework with eight iterative stages—Profile, Diagnose, Recommend, Deliberate, Human Review, Act, Evaluate and Update. The framework assigns complementary AI and human roles, embeds governance safeguards at each stage, and links the process to employability outcomes. It therefore extends existing discussions of AI-enabled career development from a technology-centred recommendation model to a human-governed, feedback-oriented employability system.

Keywords

artificial intelligence; career development; sustainable employability; employee trust; AI acceptance; career adaptability; human-AI collaboration; HRD; responsible AI

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DOI

DOI: https://doi.org/10.67061/ijcams.2026.vol.11.issue.03.8128

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