National, February 20, 2025: A study by researchers at the Max Institute of Healthcare Management (MIHM) at the Indian School of Business (ISB) has uncovered significant insights into healthcare providers’ attitudes toward artificial intelligence (AI) in tuberculosis (TB) diagnosis, highlighting both opportunities and challenges in implementing AI-based healthcare solutions in India.
Published in JMIR Formative Research, a peer-reviewed journal, the study titled ‘Understanding Providers’ Attitude Toward AI in India’s Informal Health Care Sector: Survey Study’ surveyed 406 Ayurveda, Yoga and Naturopathy, Unani, Siddha, and Homeopathy (AYUSH) and informal healthcare providers (collectively called AIPs) across Gujarat and Jharkhand. They found that while 93.7% of providers believed AI could improve TB diagnosis accuracy, only 69.4% were willing to adopt the technology.
Sumeet Kumar, Assistant Professor, Information Systems, ISB and lead author of the study said, “The gap between belief in AI’s potential and willingness to adopt it suggests that technological superiority alone may not guarantee successful implementation”. He added that regional differences and existing healthcare infrastructure play crucial roles in technology adoption.
TB remains a global health crisis, claiming 1.5 million lives in 2020 alone, with India bearing a substantial burden. Early and accurate diagnosis is key to TB treatment, but accurate diagnostic tools like molecular diagnostic tests are expensive, difficult to access and challenging to maintain. AI-augmented chest X-ray (CXR) scans offer a viable solution, especially in underserved Indian settings. Since AIPs are often the first point of contact for TB patients in India, understanding their perspectives on AI-based TB diagnosis is crucial for its effective implementation.
The key findings of the research include higher adoption readiness in Gujarat (73.4%) compared to Jharkhand (58.4%), reflecting the impact of regional healthcare infrastructure development. Providers who were more confident in diagnosing TB showed greater willingness to adopt AI. Also, providers’ trust in local radiologists influences AI adoption differently across regions.
The research suggests that successful AI implementation in healthcare requires tailored approaches considering regional infrastructure differences, additional support, and training programmes for healthcare providers, focus on providers with limited access to diagnostic infrastructure and consideration of cost implications.
Explaining the significance of this study, Professor Sarang Deo—Deputy Dean, Faculty and Research at ISB and Executive Director – MIHM, who is also the co-author of this research paper—said: “Our study shows the importance of including behavioural and implementation science elements in the evaluation of AI, moving beyond the technical aspects that currently dominate the discourse. The finding that providers with weaker diagnostic skills are less likely to adopt AI indicates that the overall impact of AI on health outcomes might be more muted than predicted by technical specifications alone.”