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A great example of technology leap-frogging is India’s 1990s adoption of GSM mobile networks. While the US was stuck with CDMA, India bypassed it in favor of GSM, which enabled widespread mobile adoption and transformative services like zero-fee payment transfers and mobile and voice banking—even in remote areas. Now, India has the opportunity to leap ahead in a similar fashion using an artificial intelligence tech stack – ML, LLMs, RAGs, Agents – or AI for simplicity, to reshape the healthcare system and deliver high-quality care more efficiently.
The Leapfrog Opportunity
AI offers India the opportunity to transform its healthcare system by bypassing incumbent models and embracing more efficient, scalable solutions, from the ground up. Just as mobile technology allowed India to leapfrog older telecommunications infrastructures, AI can enable India to overcome many of the systemic challenges facing healthcare today. AI’s capabilities in predictive analytics, diagnostics, and personalised treatment plans offer a significant advantage for a country grappling with issues like access to care, the growing burden of chronic diseases, and a shortage of trained healthcare professionals.
A well thought out roadmap can impact both infectious diseases and chronic illnesses. In a country as disparate as India, leveraging, a readily available AI service layer for things like diagnostic imaging, disease detection, or clinical decision support, providers—whether in urban or rural areas—could access the same high-quality tools and insights, effectively reducing the quality gap between different healthcare providers, without overwhelming healthcare providers with extensive training requirements.
On one hand, AI-powered systems could aid in the early detection of dengue and chikungunya outbreaks using multi-modal, cross-disciplinary data, potentially reducing the spread of the disease. On the other hand, they could manage cardiometabolic disease by creating specific sub-population prevention and management protocols, leveraging multi-omic data to improve outcomes and management as well as prevent and delay onset.
Building the AI Infrastructure for Healthcare
To realize this potential, India needs to double down on its standardized healthcare infrastructure so that it is ready for the changes coming in the next decade. Just as UPI revolutionized digital payments in India by providing a secure, interoperable platform for financial transactions, an UMANG style platform could be created for healthcare. This platform would integrate disparate data sources—behavioral, genomic, and phenotypic—creating a comprehensive and accessible data lake. The data lake would serve as the backbone for anyone – with the right credentials – to build AI applications on top of it.
India’s existing biobank efforts, like Phenome India, are an important first step, but the challenge remains in data quality and comprehensiveness. In comparison, the UK Biobank data set has empowered over 21,000 scholarly articles in 2024 alone, significantly advancing health research. Right now, the best data for making AI applications on subcontinental peoples comes from the UK!
India needs a National Institute for the Application of AI in Healthcare, a public-private-philanthropic platform to maintain and distribute AI-driven clinical protocols, decision support systems, diagnostics, and more. Government hospitals would have free access to AI tools, while private hospitals pay a nominal fee, helping to foster innovation and keep costs manageable.
Ethical Considerations
While AI holds immense potential, it is important to address the ethical challenges surrounding its use in healthcare. Issues like algorithmic bias, data privacy, and informed consent must be carefully managed to maintain public trust, ensure fairness, and adequate compensation for individual and collective data providers.
As AI plays a larger role in healthcare decision-making, clear guidelines on accountability are essential to ensure we have a clear understanding of who is responsible for those decisions. This is probably one of the harder questions to answer. Will it be the human or the algorithm? These are policy and regulatory choices that informed governments need to make quickly.
Skilling the Workforce
Realizing the vision of an AI-powered healthcare system will require a skilled workforce. To fill this gap, India needs to invest in developing a robust talent pipeline by fostering collaborations between universities, healthcare institutions, and tech companies. Training data scientists, engineers, and AI researchers is essential to ensure that India can build and maintain the AI infrastructure required for a national AI healthcare system. But larger infrastructure considerations around data storage, compute power, and energy need attention as well.
AI’s Global Leadership Potential
This Government doesn’t shy away from big ideas and if India successfully executes this vision, it could become a global leader in AI healthcare, developing solutions that are scalable and adaptable to other countries facing similar healthcare challenges. India’s diverse population, combined with its commitment to digital infrastructure, makes it an ideal environment for testing and implementing AI in healthcare. The innovations developed in India could be exported to other developing nations, positioning India as a model for equitable AI-powered healthcare.
These pieces are being published as they have been received – they have not been edited/fact-checked by ThePrint.