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Ms. Basu Kalyanwat is an Assistant Professor in the Department of Computer Science and Application at Vivekananda Global University, Jaipur, Rajasthan, India. Her research interests include AI-driven analytics, employability enhancement systems, machine learning, and educational technologies.
Enhancing Employability and Future Learning (EFL) has emerged as a paramount concern in the swiftly transforming digital economy, where skill demands perpetually evolve due to technology progress. This chapter examines how AI-driven analytics might enhance employability outcomes by providing data-driven insights on learner competencies, industry requirements, and career trajectories. It analyses how machine learning models, natural language processing, and predictive analytics can evaluate skill deficiencies, anticipate employment trends, and suggest individualised learning pathways. Principal applications encompass intelligent career counselling, resume evaluation, employment matching systems, and ongoing skill enhancement frameworks. The chapter also addresses concerns including data privacy, algorithmic bias, digital inequality, and the necessity for transparent AI systems. Emerging trends, like lifelong learning ecosystems, micro-credentialing, and AI-driven workforce intelligence platforms, are also examined. By utilising AI-driven analytics, educational institutions and organisations may more effectively connect learning results with industry requirements, hence improving employability and promoting ongoing, future-oriented learning.