From diagnostics to policy: How AI is transforming healthcare in India

Artificial intelligence (AI) is transforming industries worldwide, and healthcare in India is no exception. From AI-driven cancer screening solutions to advanced diagnostic tools for infectious diseases, India is increasingly leveraging AI to make healthcare more accessible, efficient, and precise. The technology can help health practitioners make better decisions, enabling early detection and supporting timely interventions, especially in resource-constrained and rural areas.

The Indian government has been actively integrating AI into the public health ecosystem, for instance, by designating AIIMS Delhi, PGIMER Chandigarh, and AIIMS Rishikesh as ‘Centres of Excellence for Artificial Intelligence,’ and through initiatives like the Media Disease Surveillance system, the Clinical Decision Support System in eSanjeevani, and AI-driven TB screening tools such as ‘Cough Against TB.’ 

However, the country continues to face a significant gap in healthcare access, reflected in its doctor–patient ratio. The country’s doctor-to-population ratio is estimated at 1:811, compared to the WHO-recommended benchmark of 1:1000, highlighting both workforce pressure and uneven distribution of medical professionals. Combined with infrastructure gaps and regional disparities, these challenges make it crucial to understand what AI can realistically achieve, where it can meaningfully bridge gaps, the barriers to scaling such solutions, and how it can shape the future of healthcare delivery across India.

How can India leverage AI for health? 

Dr Mona Duggal, Director at ICMR–National Institute for Research in Digital Health and Science, stressed that AI can significantly strengthen healthcare screening at the grassroots level, especially by empowering frontline health workers.

She explained that the challenge is not always the absence of doctors, but their limited physical reach. “Doctors are not always available at the doorstep. At the doorstep, it is the frontline workers who play a crucial role. If AI tools can support them, screening coverage can improve substantially,” she said.

However, Dr Duggal cautioned that expanding screening must go hand in hand with strengthening referral and treatment systems. “When screening improves, the number of people entering the health system will rise. That means we must ensure the system is ready to handle this demand, from referrals to follow-up care,” she noted.

Highlighting the role of AI as a support tool rather than a replacement for clinicians, she added, “AI and data analytics should work as supporting technologies. The final diagnosis and clinical decisions must always remain with the doctor who is the captain of the ship.” 

She stressed that AI-generated responses should never be treated as medical advice. “Just like lab reports need clinical correlation, AI outputs also need professional validation. These are not final answers,” she cautioned.

Adding to this, Dr Shrishendu Mukherjee, MD at the Wadhwani Foundation, underlined that AI’s role in healthcare goes far beyond individual diseases and must be viewed across the full spectrum of prediction, prevention, and patient management.

He pointed out that AI enables predictive healthcare by identifying early risk markers. “Through biomarkers and large-scale data analysis, AI can help predict conditions such as pre-diabetes, high cholesterol, cardiovascular risks, and even pre-term birth,” he said, emphasising the importance of studying large population cohorts to build reliable predictive models.

Dr Mukherjee explained that prediction must be followed by prevention. “Once a person is identified as high-risk, prevention strategies become critical. Using AI-enabled research, we can assess which interventions actually work and help stop diseases before they progress,” he added.

He also highlighted AI’s growing role in managing India’s massive patient population, from digital patient databases and prescription management to diagnostics such as X-rays and vein-identification technologies. “With a population of 1.4 billion, India needs robust datasets. These datasets must be converted into strong algorithms, validated scientifically, certified, and only then implemented at scale,” he said.

Dr Mukherjee acknowledged that while progress has begun, a major challenge remains the lack of digitisation. “India already has vast health data, but much of it is not digitised. The first step is to bring this data into digital systems so it can be meaningfully used,” he noted, adding that platforms such as the AI Impact Summit can help shape future strategies for AI-driven healthcare transformation.

Challenges: Will AI bridge the digital divide or widen it?

Dr Mukherjee acknowledged that India continues to face a significant digital divide but expressed cautious optimism about its gradual narrowing. “There is a strong digital divide, I won’t deny that. But if you look at smartphone penetration and digital access, this gap is slowly coming down,” he said.

He highlighted the critical role of frontline health workers in ensuring that AI-driven healthcare tools reach underserved populations. According to him, empowering ASHA workers and community health staff can help translate technology into real-world impact.

“When frontline workers such as ASHA didis are digitally enabled, they become the bridge between technology and the community. If we reduce their paperwork burden and simplify data collection, healthcare delivery at the village level becomes much more efficient,” Dr Mukherjee noted.

Drawing on India’s COVID-19 response, he pointed out that digital platforms played a key role in managing large-scale public health challenges. “During COVID, India managed vaccination and monitoring at a scale that became a global example. Digital tools were central to that success. Moving from digital healthcare to AI-enabled healthcare is the natural next step,” he said.

However, Dr Mukherjee also flagged the growing trend of self-diagnosis through AI tools such as ChatGPT as a potential risk. “It is a challenge. Today, people use AI to self-diagnose, just like earlier, they would read medicine leaflets and make assumptions. This can lead to misuse, for example, taking antibiotics unnecessarily for fever,” he warned.

In fact, Antimicrobial Resistance (AMR), driven largely by the overuse and misuse of antibiotics, has emerged as a major public health threat in India. Estimates suggest that over 3 lakh people have died every year since 1990 due to drug-resistant infections. In 2021 alone, around 2.67 lakh deaths were directly attributable to AMR, while nearly 9.87 lakh deaths were associated with antimicrobial resistance, underscoring the scale of the crisis.

Dr Mukherjee added that limited doctor availability and high patient-to-doctor ratios often push people towards self-treatment. “Getting appointments is difficult in many places. Until these systemic issues are addressed, this behaviour will continue. That is why public education must evolve alongside AI adoption,” he said.

Highlighting another major challenge, Dr Duggal drew attention to the stark divide between rural and urban healthcare ecosystems, particularly in how health data is collected, managed, and utilised across these settings.

She explained that, as researchers, data collection in rural areas is easier as healthcare largely operates through structured public systems such as primary health centres and community health centres, supported by large networks of ASHAs and frontline workers. In contrast, urban healthcare is fragmented across public and private providers due to immigration.

“There is a clear divide. In urban areas, a large population also depends on private healthcare, and many are now consulting online, while another segment uses public facilities. The disease patterns we see are also very different,” Dr Duggal said.

Sharing an example from a recent hospital visit, she noted that a private hospital was observing a high number of lifestyle-related illnesses among IT sector employees, largely due to odd working hours and sedentary lifestyles. “This difference in patient profiles reflects unequal access and varying health behaviours,” she said. 

According to Dr Duggal, integrating data from rural and urban, public and private health systems can enable evidence-based policymaking and more precise healthcare interventions. “If AI models are trained on comprehensive datasets, healthcare can become far more targeted and precision-driven,” she added.

Commenting on a widely reported 2025 case from Texas, in which a 23-year-old university student allegedly died by suicide after interacting with ChatGPT, which reportedly reinforced his distress instead of directing him to professional help, Dr Duggal raised serious concerns about the absence of strong regulatory guardrails, especially for vulnerable users such as children.

“People often upload personal data without understanding privacy risks. They seek quick answers, but these platforms do not take responsibility for outcomes. Until stronger policies and regulations are in place, awareness is our biggest safeguard,” she emphasised. 

What is the way forward?

Speaking at the fourth edition of the Health of India Summit 2026, National Health Authority (NHA) CEO Dr Sunil Kumar Barnwal highlighted how artificial intelligence can play a transformative role in strengthening India’s healthcare infrastructure.

“We all know the way AI will change healthcare delivery. It will change how patients receive treatment, how doctors handle clinical cases, and how the capacity of health professionals improves,” Dr Barnwal said, adding that AI can also significantly reduce the non-clinical workload of healthcare workers.

Placing citizens at the centre of digital health reforms, he underlined two core concerns that AI-driven healthcare must address. “We have to keep citizens at the centre and ask, what are the basic questions in their minds? The first is timely, quality healthcare. The second is whether a health issue will push a family into financial distress. If we can answer these two questions, AI in healthcare will grow in the right direction,” he said.

Highlighting the impact of Ayushman Bharat, Dr Barnwal shared that “over the past seven years, more than 40 crore Ayushman cards have been issued, enabling over 11 crore hospital admissions and generating Rs 1.65 lakh crore in savings by reducing out-of-pocket expenditure for citizens.”

“These numbers matter because of India’s population size. But what matters even more is that fewer families are now forced to sell assets, take high-interest loans, or delay treatment until it becomes an emergency. We must ensure dignity in access to healthcare,” he added.

However, Dr Barnwal cautioned that financial protection alone is not enough. He emphasised the need to move beyond fragmented, episodic hospital visits towards an integrated and continuous care model. “A healthcare journey is not just one hospital visit. A patient needs multiple touchpoints - diagnostics, treatment, and follow-ups. That is where the Ayushman Bharat Digital Mission, launched in 2021, becomes critical,” he said.

According to him, the mission focuses on building digital infrastructure before onboarding systems, enabling seamless connectivity across stakeholders. “This IT backbone allows health systems to talk to each other, keeps the patient at the centre, identifies healthcare professionals and facilities, and ensures every care episode is recorded and remains with the patient,” he explained.

Dr Barnwal further outlined how AI-enabled digital systems can improve everyday healthcare delivery. “Can chronic patients receive timely alerts on their phones? Can a mother access her child’s health records instantly during emergencies? Can doctors and nurses spend more time on clinical care instead of non-clinical work like other administrative work? Can governments track disease trends and possible outbreaks? These are the questions AI must help us answer,” he said.

Describing India’s digital public infrastructure as the foundation for AI innovation, he added, “We have built the guardrails. Now we need to let more trains run on these tracks, responsibly and at scale.”

Dr Barnwal also highlighted AI’s potential in empowering frontline healthcare workers. “We are looking at AI as a big opportunity for building the capacity of frontline health workers, and ASHA workers can actually segregate a chronic patient from a normal patient. They can ensure and make sure of some kind of early detection of a severe disease that they may be likely to have,” he said.

Emphasising the importance of context-specific innovation, he noted that building Indian datasets is crucial for developing accurate disease prediction models tailored to the country’s diverse population.

Dr Barnwal announced that the National AI Strategy for Health will be launched during the upcoming India AI Impact Summit, which will lay the roadmap for responsible and ethical deployment of AI in healthcare.

This story is done in collaboration with First Check, which is the health journalism vertical of DataLEADS.