Year: 2026
Type: article
Abstract: Assessment in Indian healthcare education continues to rely heavily on traditional examiner-dependent methods that are difficult to standardize in high-volume training environments. Shortage of faculty, enhancement in the intake of students, and resource-intensive competency-based assessments have created significant challenges in maintaining fairness, reliability, and scalability. Artificial intelligence (AI)-enabled assessment tools offer promising solutions through automated grading, simulation-based training, remote proctoring, and AI-assisted OSCE evaluation. Although AI integration in border higher education has regulatory and infrastructural limitations. Hybrid assessment models coming AI-assisted evaluation with faculty oversight may improve objectivity. Pilot implementation of AI-suppurated systems in Indian healthcare institutions could generate evidence regarding reliability, bias reduction, and efficiency. Integrating AI into healthcare assessment is essential for developing a competent, future-ready healthcare workforce aligned with the digital transformation of modern healthcare systems.
Author: Anita Rani Singh
Institution: King George's Medical University
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W7166668929