By Tejesvi Rao Veerapalli, Chief Executive Officer, Apollo Hospitals, Hyderabad: Healthcare was reactive by nature. But AI and Big Data are proving otherwise, showing us that care can be Predictive, Personalized, and PRO active.
We are standing at the cusp of a healthcare revolution. Now, we’re no longer asking if we can predict illness — we’re asking how early we can intervene.
This isn’t speculation. It’s a transformation. Artificial Intelligence (AI) and Big Data are no longer just buzzwords; they are the new engines of precision medicine, helping us shift from treatment to prevention.
The Data Boom: From 153 to 2,314 Exabytes
In 2013, global healthcare data stood at 153 exabytes. By 2025, it’s expected to cross 2,314 exabytes (IDC).
That’s over a 15x increase in just over a decade. In India, this surge is reflected in the expansion of EHRS, wearable devices, digital health records, and genomic research, with initiatives like the Ayushman Bharat Digital Mission accelerating this transformation.
Traditional analytics can’t keep up — but AI can. It helps uncover hidden patterns, predict health risks, and personalise care like never before.
Diagnosing Earlier, With Greater Precision
Early detection is one of AI’s most powerful promises. In India, platforms like Qure.ai are leading the way — enabling faster diagnosis of chest X- rays and head CTs for conditions like tuberculosis, stroke, and COVID-19.
Similarly, Niramai’s AI-based breast cancer screening uses thermal imaging, making screening more accessible and non-invasive.
These innovations are critical in a country where late diagnosis is one of the leading causes of preventable deaths. AI is helping bridge the gap — delivering faster, smarter, and more accurate diagnoses.
Chronic Disease Management: Real-Time, Real Impact
Chronic conditions — diabetes, heart disease, hypertension — account for 71% of global deaths, as per the WHO.
AI-powered platforms like Livongo are changing that. By analyzing data from wearables — heart rate, glucose levels, sleep patterns —these platforms predict deterioration before it escalates.
A 21% drop in medical spending among its users. That’s not just smarter healthcare — it’s more sustainable healthcare. Chronic conditions — like diabetes, hypertension and heart disease — account for over 62% of deaths in India (ICMR).
Startups such as BeatO and HealthifyMe are leveraging AI to help users monitor vitals, track patterns, sleep patterns and receive real-time alerts.
These platforms enable early intervention and better disease management — without needing to step into a hospital. It’s not just smarter healthcare. It’s more affordable, accessible, and sustainable.
Smarter Hospitals with Predictive Intelligence
AI isn’t just transforming care— it’s reimagining hospital operations. From predicting ER congestion to forecasting ICU demand and even surgical recovery rates, AI is enabling real-time decision-making. Better care, optimized resources, and reduced costs — the trifecta of modern healthcare.
The Double-Edged Sword: Challenges to Consider
- Data Privacy: How do we ensure ethical use of personal health data?
- Algorithmic Bias: Are AI systems trained on representative, diverse datasets?
- Integration: How do legacy systems keep up with intelligent infrastructures?
These aren’t just technical issues — they’re human ones. Solving them requires a collaboration across clinicians, technologists, regulators, and patients.
- Think Systems, Not Silos – Collaborative care powered by interoperable platforms is the future.
- Champion Change from Within – Be the advocate who drives responsible AI adoption in your organization.
- Partner with Tech, Not Against It – AI won’t replace doctors, but doctors using AI will
redefine the standards of care.
Final Thought: Innovation Is the Heartbeat of Modern Healthcare
Innovation isn’t just about new tools — it’s about a new mindset. In a world of increasing complexity, the only sustainable way forward is through adaptability, collaboration and a bold willingness to reimagine what healthcare can be.
AI and Big Data aren’t the future — they are the present. And how we respond will define not just our systems, but the health of our society at large.
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