The Algorithmic Colleague: A Vision for AI-assisted Rheumatology in India

Abstract

Rheumatic and musculoskeletal diseases (RMDs) are an escalating cause of disability in India, a burden managed by a critically limited specialist workforce. This imbalance, particularly in non-urban settings, contributes to diagnostic delays and suboptimal outcomes. Artificial intelligence (AI) is increasingly explored as a decision-support tool with the potential to augment clinical capacity across the continuum of rheumatology care. This narrative review synthesises contemporary evidence to examine the current landscape of rheumatology services in India and to outline key AI paradigms relevant to clinical practice. We discuss emerging applications in diagnostic support, disease monitoring and workflow optimisation, while critically examining limitations related to model interpretability through the lens of retrieval-augmented generation architectures. Significant implementation challenges remain, including fragmented health data, medico-legal uncertainty under the Digital Personal Data Protection Act, 2023 and the ‘prediction-reasoning gap’, wherein AI systems may produce correct outputs via clinically unsound reasoning pathways. We propose a calibrated vision for AI not as an autonomous authority, but as a supervised ‘algorithmic colleague’ that complements clinical expertise, supported by investments in representative data infrastructure and clinical AI literacy tailored to the Indian context.

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