Economic Survey 2024-25 Highlights Challenges & Opportunities for AI in Indian Healthcare

The National Strategy for Artificial Intelligence (2018), developed by NITI Aayog, envisioned AI as a powerful tool to bridge healthcare gaps.

The Economic Survey 2024-25, tabled in Parliament on Friday, has highlighted both the immense potential of artificial intelligence (AI) in Indian healthcare and the challenges that hinder its widespread adoption.

While AI is expected to enhance accessibility, affordability, and quality of healthcare, the report identifies key obstacles such as a shortage of specialized talent, data complexities, and difficulties in scaling AI solutions.

The National Strategy for Artificial Intelligence (2018), developed by NITI Aayog, envisioned AI as a powerful tool to bridge healthcare gaps.

The report described AI, when combined with robotics and the Internet of Medical Things (IoMT), as the “new nervous system” of healthcare, capable of transforming medical diagnosis, treatment, and patient care.

According to the survey, AI adoption in healthcare can significantly reduce drug discovery costs, improve the quality of medical devices, enhance diagnostic accuracy, and enable real-time monitoring of patients in remote areas.

Additionally, AI-driven technologies can help streamline patient journeys, assist clinicians in reducing misdiagnoses, and enable personalized treatments and preventive care.

Rajasthan’s AI-Based Silicosis Detection Model

The survey highlighted how Rajasthan has successfully integrated AI into its public health management system to tackle Silicosis, a severe lung disease caused by inhaling silica dust, which is prevalent in the state due to extensive sandstone mining activities.

The Rajasthan government has effectively deployed digital X-rays, teleradiology, and AI to streamline the disease diagnosis process.

The AI model was trained using an extensive dataset of labeled chest X-rays, enabling automated and more accurate disease detection.

This AI-driven technology has significantly improved the speed and accuracy of Silicosis diagnosis, leading to better patient outcomes and timely medical intervention.

To further assist Silicosis patients, the state government introduced a Direct Benefit Transfer (DBT) self-approval portal, allowing diagnosed individuals to receive financial assistance directly into their bank accounts.

By eliminating bureaucratic hurdles, the system ensures that affected individuals get the support they need without unnecessary delays.

Silicosis is associated with serious comorbidities, including tuberculosis, cancer, ischemic heart disease, bronchitis, and infections.

The AI-driven diagnostic model, along with financial aid for patients, represents a comprehensive approach to managing the disease and supporting those affected.

eSwasthya Dham Portal for Pilgrim Healthcare

Another initiative recognized in the survey is Uttarakhand’s eSwasthya Dham portal, which is designed to monitor the health of Char Dham Yatra pilgrims visiting Yamunotri, Gangotri, Kedarnath, and Badrinath.

This digital health platform tracks pilgrims' health parameters and provides emergency medical support when required.

The system also enables visitors to create an Ayushman Bharat Health Account (ABHA) within minutes, giving them a secure digital identity to store and manage health records.

This initiative ensures that pilgrims receive timely medical assistance and helps health authorities respond effectively to medical emergencies during the pilgrimage.

Current Status of AI Adoption

While India has made progress in AI-driven healthcare, the Economic Survey 2024-25 noted that the adoption of AI is still in its early stages.

In 2023, only 34% of healthcare organisations were piloting AI projects, and just 16% had moved their generative AI initiatives into production.

Despite the increasing interest in AI applications, several challenges continue to hinder its widespread adoption.

The shortage of specialised AI talent—both in technical expertise and domain knowledge—remains a significant barrier.

Additionally, the complexity of managing and integrating vast amounts of healthcare data poses difficulties in scaling AI solutions across the healthcare sector.

The report emphasized the need for strategic interventions to address these issues.

Strengthening policies, fostering collaborations between the government, private sector, and research institutions, and investing in AI-driven healthcare infrastructure will be essential in overcoming these obstacles.

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