A Global Renaissance: Artificial Intelligence in Preventive Healthcare
15-05-2026
A radiologist opens a chest X-ray in a tertiary hospital; even before the doctor scans the report, a faint red box flickers, flagging a 3mm nodule in the upper lobe of the left lung—almost invisible to the human eye. What once relied on clinical experience alone is now instantly augmented by Artificial Intelligence (AI). This is not science fiction; it is healthcare reality in 2026.
Defined as the science of building machines capable of mimicking human intelligence, AI is rapidly transforming healthcare worldwide. As highlighted in the Future Healthcare Journal (Bajwa et al. 2021), AI has the potential to reshape and redefine the practice of medicine and healthcare delivery. In India, this transformation is gaining momentum. This growth reflects not just technological progress but a deeper shift in how healthcare systems are evolving to meet the rising demands. The AI healthcare market is expected to grow from USD 1.6 billion in 2025 at a CAGR of 40.6% to reach USD 34.35 billion by 2034 (IndiaAI, 2024). According to the Healthcare Industry Report (IBEF, 2025), Digital Health and Telemedicine are emerging as key growth drivers; the market valued at USD 8.79 billion in 2024 is projected to reach USD 47.80 billion by 2033 at a CAGR of 17.67%.
Healthcare systems worldwide are under pressure to achieve the “Triple Aim” - improving population health, enhancing patient experience, reducing costs, and improving the work-life of healthcare providers (Berwick et al., 2008). This was later expanded to the “Quadruple Aim,” which includes improving the work-life of healthcare providers (Bodenheimer & Sinsky, 2014). A McKinsey & Company report (2025) estimates a global shortage of 10 million healthcare workers by 2030. In India alone, an additional 2.7 million healthcare professionals are needed. In this context, AI exhibits potential and emerges not as a luxury but as a necessity. While some interventions can roughly add workers to the healthcare workforce, they are not enough to bridge the gap.
The Global Monitoring Report (World Bank & WHO, 2025), track Universal Health Coverage (UHC) globally using the UHC Service Coverage Index (SCI). While the global index rose from 54 to 71 points between 2000 and 2023, the report warns that progress has significantly slowed since 2015, highlighting the urgent need for sustained investment to meet the 2030 Sustainable Development Goal targets.
From “reactive treatment” to “preventive intelligence”
New job roles such as telehealth professionals, AI specialists, health data scientists, and precision medicine experts are in demand, along with telemedicine specialists, digital health professionals, and health IT experts. This has increased due to the growing adoption of digital health solutions (CII - Centre of Excellence on Skills, 2025). As the industry adopts more AI-driven diagnostics, telemedicine, and digital health solutions, technology and digital skills will become indispensable.
Over the last decade, technology has significantly transformed the healthcare ecosystem directly shaping the way healthcare is perceived; prioritising “preventive healthcare” over “reactive response”. Beyond diagnostics and public health systems, a new and transformative role for AI is emerging—one that positions it as a “continuous health companion”. Wearable technologies and mobile health platforms are generating datasets, enabling real-time health monitoring. These micro-interventions, though subtle, can significantly improve long-term health outcomes. With higher disposable income, better health insurance, greater health awareness, and a shift towards preventive care, perceptions of health have changed.
According to the World Population Ageing 2019 (Department of Economic and Social Affairs, United Nations, 2019), 1 out of every 6 people are predicted to be over 65 by 2050 and the 80+ group is expected to triple, over the next 30 years. Individuals aged 55+ currently account for more than half of health spending (Peterson-KFF Health System Tracker, 2026) and this group is expected to benefit most from earlier targeted prevention. Ageing itself is not the crisis; it is only a catalyst, with the real challenge being that health systems intervene too late.
In India, this shift of making preventive healthcare more inclusive, can have far?reaching impact. With access to specialists remaining uneven, AI-powered screening tools enable frontline healthcare workers to perform advanced diagnostics in rural and underserved regions.
Government role in AI adoption
Government initiatives and schemes have also evolved from foundational digital health strategies to targeted AI deployment, with significant acceleration between 2022 and 2026 (PIB, 2026). Since 2017, India has rapidly integrated AI into public healthcare through the National TB Elimination Programme (early detection of TB outcomes), the Media Disease Surveillance System (outbreak alerts), platforms such as eSanjeevani (AI-assisted consultations), and initiatives like MadhuNetrAI (community-level screening). NITI Aayog and the Ayushman Bharat Digital Mission (2020–21) established a national digital health ecosystem to increase AI adoption across public health systems. The India AI Mission and Centres of Excellence (2025) accelerated innovation, while 2026 efforts emphasise workforce training, validation platforms (SAHI, BODH), and integrated care through the National One Health Programme. (PIB, 2026)
The AI Impact Summit 2026 was a step towards establishing the transformative role of AI in advancing public health outcomes. Emphasis on “AI for development”, responsible governance, and sectoral applications in healthcare, agriculture, and public services were some of the key highlights of this Summit.
Challenges and Way Forward
For India, the AI framework holds immense promise in making preventive healthcare more inclusive. However, challenges remain with data privacy, cybersecurity, algorithmic bias, and the risk that technology-driven solutions may not reach all sections of society equally.
Despite the enthusiasm, 80% of the healthcare sector professionals acknowledge that their organisations are not fully ready to realise AI's full potential (EY Parthenon, 2024). In many low- and middle-income settings, limited adoption of electronic health records reduces the use of the available datasets increasing the risk posed by AI systems (Xang, X. et al., 2024). Biased data collection leads to discrimination, reduced accuracy, and the widening of health inequalities. Calibration is further complicated by differences in disease prevalence across regions with varied treatment paths and medical knowledge, making consistent performance difficult to achieve. (Xang, X. et al., 2024)
A major issue is the “black box” nature of AI, where decisions are not explainable, raising accountability questions in cases of incorrect diagnoses. While AI can outperform doctors in some tasks, responsibility often falls on physicians, potentially limiting patient autonomy and explainability. Patient acceptance may also decrease if AI-driven advice is not clearly justified (Naik, N. 2022).
Conclusion
As India continues to navigate its healthcare challenges, the integration of AI emerges as a beacon of hope and innovation. With careful planning, ethical governance and collaborative efforts, it can significantly enhance the quality and accessibility of healthcare services in India. It is an opportunity to transform the healthcare landscape, making it more resilient, efficient and inclusive (EY Report, 2024).
The 2025-2026 period marks a “maturation” phase, with AI’s promise to proving its return on investment (ROI) and establishing governance. Hospital-centric care is giving way to home-based monitoring, with AI’s single agenda: ensuring sharp decline in hospital visits.
India could fully utilise the benefits of AI in its healthcare industry by making smart investments, enacting growth-friendly government policies, and encouraging collaboration among players. AI is not replacing healthcare professionals; it is augmenting their capabilities. The future of healthcare lies in collaboration between human expertise and machine intelligence, where clinicians provide empathy and judgment, and AI delivers precision and predictive insights.
References
Bajwa, J., Munir, U, Nori, A. & Williams, B. (2021). Artificial Intelligence in Healthcare: Transforming the Practice of Medicine. Future Healthcare Journal. 8 (2) 88-194.
https://pmc.ncbi.nlm.nih.gov/articles/PMC8285156/pdf/futurehealth-8-2-e188.pdf
Jeevanandam, N. (2024). AI in Indian healthcare: Emerging trends and opportunities in 2025. IndiaAI.
https://indiaai.gov.in/article/ai-in-indian-healthcare-emerging-trends-and-opportunities-in-2025
IBEF. (2025). India Industry Report.
https://www.ibef.org/download/1770035033_Healthcare-November-PPT-2025.pdf
Donald M. Berwick, Thomas W. Nolan, and John Whittington. (2008). The Triple Aim: Care, Health, And Cost. Health Affairs. 27 (3).
https://doi.org/10.1377/hlthaff.27.3.759
Bodenheimer, T. & Sinsky, C. (2014). From Triple to Quadruple Aim: Care of the Patient Requires Care of the Provider. The Annals of Family Medicine. 12(6), pp. 573-576.://doi.org/10.1370/afm.1713
https://indiaai.gov.in/article/ai-adoption-and-healthcare-in-india-an-overview
Kumar, P., Holt, T., Wong, Y. & Kimeu, M. (2025). Heartbeat of health: Reimagining the health workforce of the future. McKinsey Health Institute.
World Bank Group and World Health Organization. (2025). Tracking Universal Health Coverage. 2025 Global Monitoring Report.
CII. (2025). The Future of Healthcare in India: Bridging Workforce Gaps and Embracing Digital Innovation.
https://www.ciiskills.in/blog/Future-of-Healthcare-in-India-Bridging-Workforce-Gaps
World Population Ageing 2019. United Nations Department of Economic and Social Affairs. https://doi.org/10.18356/6a8968ef-en
McGough, M., Telesford, I., Cotter, L., & Claxton, G. (2026). How do health expenditures vary across the population? Peterson-KFF Health System Tracker.
https://www.healthsystemtracker.org/chart-collection/health-expenditures-vary-across-population/
PIB Release. (2026). Transforming Healthcare Delivery Through Artificial Intelligence. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2227410®=3&lang=1
Wang, X, Xi Zhang, N., He, H., Nguyen, T., Kun-Hsing, Y., Hao, D., Brandt, C., Bitterman, D.S., Pan, L., Cheng, C., Zou, J., & Dianbo, L.L., Safety challenges of AI in medicine. (2024).
https://www.researchgate.net/publication/384502205_Safety_challenges_of_AI_in_medicine
Naik, N., Hameed BMZ, Shetty, D.K., Swain, D, Shah, M., Paul, R., Aggarwal, K., Ibrahim, S., Patil, V., Smriti, K., Shetty, S., Rai BP, Chlosta, P., Somani B.K. (2022). Legal and Ethical Consideration in Artificial Intelligence in Healthcare: Who Takes Responsibility? Front Surgical. 9.
EY Parthenon (2024). Chaos to Coherence. https://www.ey.com/content/dam/ey-unified-site/ey-com/en-in/insights/health/documents/ey-p-healthcare-gen-ai-report-chaos-to-coherence.pdf
---------------------------
Manisha Dhulipala is a Senior Research Fellow at CDPP.
