Indian Healthcare Will Likely ‘Uberify’: Here’s Why
Cautionary Note: Please don’t interpret any of this as a recommendation for you to do what I did. I’m fully aware of the risks I’m taking with my health when I undergo certain procedures or take medications. Always consult a qualified healthcare professional for your own medical decisions.A (Literal) Heart-to-Heart with AI
In early November 2024, during a routine “master health checkup” in India—the kind that costs just a few thousand rupees ($20-30)—my ECG showed a peculiar waveform. Rather than wait to deal with it after I got back to the US or meet a doctor to talk about it, I decided to put an AI tool I had been testing (and funding) for the last several months through its paces. The tool, called Apna Vaidya, is a conversational AI “co-pilot” that assists individuals with medical questions and a whole lot more.
The tool flagged something concerning and recommended cardiac imaging. What happened next showcases why India could revolutionize AI healthcare: Within 24 hours, I had completed an Echocardiogram, CT angiogram, and cardiac MRI (all recommended one after the other by the tool itself based on the results from the previous test)—all booked under my “cardiologist” Dr. Arvind Iyengar (AI). I chose this playful name over just listing “self” as the referring doctor, which would have been equally valid. No pre-authorization, no insurance sign-off, just a phone call and in one case just a WhatsApp message. Finally, the tool’s preliminary diagnosis of mild myocarditis which was later confirmed by cardiologist friends when they reviewed the AI notes along with the raw data, the doctors also signed off on the relatively benign anti-inflammatory medication that the AI had recommended.
This wasn’t my first AI-guided medical adventure in India. In August 2023, persistent headaches and jaw pain led me to consult GPT-4, which guided me through a series of blood tests from Orange Health, imaging studies, and even a thyroid FNA (fine-needle aspiration) biopsy—all accomplished without a doctor’s visit and for around $150. The AI’s diagnosis of subacute thyroiditis and suggested treatment proved spot-on, with symptoms resolving within days and thyroid functions returning to normal in about 12 weeks (confirmed in the US with some tests that ended up costing a few hundred dollars).
These experiences weren’t just lucky breaks—they exemplify why India is uniquely positioned to enable the use of AI to revolutionize consumer healthcare. The ingredients are all in place: a very relaxed regulatory environment, cultural acceptance of direct healthcare access, and a massive population ready as well as in need for innovative solutions. As I see it, the rocket has all the fuel; someone just needs to light it and watch it reach Mars.
India’s Regulatory Climate — A Launchpad for AI Healthcare
My ability to navigate India’s healthcare system with such ease wasn’t just luck – it represents a unique intersection of regulatory freedom and cultural attitudes that makes India fertile ground for AI innovation in healthcare. While my experiences might seem surprisingly frictionless to Western readers, they actually exemplify how Indians traditionally approach healthcare.
Take telemedicine, for instance. When COVID-19 hit, Western countries struggled with complex regulations around virtual care. This openness isn’t just anecdotal: According to a recent Telemedicine Society of India report, telemedicine usage grew by over 3,000% from 2020 to 2022, propelled by India’s world-leading mobile data consumption (more than 14 GB per person per month). Platforms sprang up overnight to meet surging demand, and regulations generally followed suit. It’s precisely this organic, market-driven adoption that positions India as an exceptional sandbox for AI-based direct-to-consumer healthcare solutions. Meanwhile, in India, platforms like Tata 1mg, Practo, DocsApp, and Apollo 24/7 simply expanded their existing services. Today, these platforms serve millions of Indians monthly, particularly in urban areas. There was no lengthy debate about telemedicine regulations – the platforms grew organically to meet demand, and the regulations followed the market’s lead.
This flexibility extends deep into how Indians access healthcare services. During my cardiac adventure, I was struck by how the diagnostic centers barely blinked at my self-referral. In most Western countries, getting an MRI without a doctor’s referral would be like pulling teeth. In India, it’s Tuesday. This isn’t just about loose regulations – it reflects a cultural belief that individuals should have direct access to healthcare tools. With 350-400 million middle and upper-middle-class Indians who can afford private healthcare, this direct-access model has spawned innovative diagnostic startups like Orange Health, which brings lab tests to your doorstep with results delivered digitally within hours.
The medication landscape tells a similar story. Apart from controlled substances like opioids or those that are extremely addictive, most medications in India are accessible without formal prescriptions. This isn’t chaos – it’s pragmatism. When I dealt with my thyroid issue, the ability to quickly get the medication I needed, verified by AI recommendations, meant I could start treatment immediately rather than waiting days for appointments and approvals. This accessibility has enabled companies like PharmEasy and Tata 1mg to create sophisticated medication delivery services with subscription-based chronic care programs.
But perhaps the most significant cultural difference is Indians’ habit with paying out-of-pocket for healthcare. When I paid for my cardiac tests without involving insurance, I wasn’t doing anything unusual – I was participating in a deeply ingrained aspect of Indian healthcare culture. While health insurance penetration is growing (currently about 37%), the middle and upper-middle classes often prefer direct payment for routine healthcare. This isn’t just about avoiding paperwork – it’s about control and immediacy. Need a CT scan? Walk in and get it done. Want to consult a specialist? Book directly. This direct payment culture removes a crucial barrier to AI-driven healthcare innovation: the need to navigate complex insurance approval systems.
The government’s ambitious Ayushman Bharat program might eventually bring more structure to this system, particularly through digital prescriptions and record management. However, cultural resistance to increased “red tape” around personal healthcare choices—coupled with India’s extremely fragmented infrastructure—makes it unlikely that this flexible system will disappear anytime soon. Companies like Tata 1mg and Orange Health demonstrate that with the right tools and partnerships, there’s immense potential in this direct-to-consumer healthcare space.One could also hope that the “forward looking” govt of india might want to integrate some of these AI assisted tools into Ayushman Bharat itself, but that might not happen considering how resistant some fairly powerful individuals in indian govt are to AI.
This combination of regulatory freedom and cultural acceptance of direct healthcare access creates a unique environment where AI can thrive. When you remove the gatekeepers and empower individuals to make their own healthcare decisions, you create a perfect testing ground for AI-driven healthcare innovation.
Structural Healthcare Challenges In India
Despite India’s uniquely accessible healthcare system, with its flexible regulations and cultural openness to direct healthcare access, the country still faces significant healthcare delivery challenges. The sheer scale of India’s population, combined with various socioeconomic factors, has created gaps that even the most efficient healthcare systems would struggle to address.
Consider the sheer scale of India: with a population of around 1.4 billion individuals and slightly less than a million doctors, the country has only one doctor for every 1,400-1,600 people – far below the World Health Organization’s recommended ratio of one doctor per 1,000 people. When you consider the fact that most of these doctors are in Tier 1 cities in India, the ratio is much worse in Tier 2, 3, or rural regions. Each year, India’s medical colleges produce between 90,000-110,000 new MBBS (Bachelor of Medicine, Bachelor of Surgery) graduates, but this barely keeps pace with the growing population. During my visits to a major hospital in Mumbai, I witnessed waiting rooms that looked more like railway stations during rush hour. Doctors often see upwards of 100-200 patients daily, with consultations sometimes lasting mere minutes. This isn’t by choice – it’s a brutal necessity in a country where there are only 0.7-1.4 hospital beds per 1,000 people, less than half of the WHO’s suggested three beds per 1,000. A related point that I learned in Tata Memorial Hospital is that they prefer to do CAR-T cell therapy rather than bone marrow transplant in patients, driven by the shortage of beds issue, but that is a topic for another time.
Even more telling is the state of junior doctors in this system. A young MBBS graduate, after 5.5 years of rigorous study, during their extended residency period, which can go for up to 3 years, starts with a monthly salary of ₹15,000-35,000 ($200-450) – comparable to what a diligent Uber driver might make in a city like Mumbai or Bangalore, which is approximately $700. In private hospitals, these junior doctors might earn slightly more, around ₹40,000-60,000 ($500-$750), but often with longer hours. “We are overworked, underpaid and spend more time doing paperwork than seeing patients,” a junior doctor told me. “And at the end of the month, my Uber driver friend makes more than I do.” This reality is particularly stark when you consider that even after completing their residency and becoming junior consultants, many doctors in the private sector start at just ₹80,000-1.5 lakh per month, despite their years of specialized training. It is only if the doctor starts a highly regarded private practice or joins Large Corporate Hospitals—something only a very small percentage of doctors achieve—do they get what can be regarded as a “great” salary; the rest get stuck at what would be 2-3x that of an Uber driver or an entry-level software engineer.
This pressure cooker environment is particularly acute in Tier 2 and Tier 3 cities. Patients frequently share wards or travel long distances to access decent facilities. One hospital administrator in Pune shared (personal communication) how they regularly operate at 150% capacity, with patients sometimes receiving treatment in corridors. The situation in rural areas is even more challenging, where basic healthcare access remains a luxury – reflected in the stark disparity of the nurse-to-patient ratio, which stands at 1.7-2.1 nurses per 1,000 population, well below the WHO’s recommendation of 3 nurses per 1,000.
These challenges present a unique opportunity for innovation, particularly in AI-driven healthcare solutions. The existing flexibility in India’s healthcare system, combined with these unaddressed needs, creates fertile ground for transformative solutions. When doctors are overwhelmed by patient volume, AI-driven tools could help them work more efficiently. When patients face long waits for specialist consultations, AI-assisted preliminary diagnoses could help prioritize cases more effectively.
Interestingly, India’s vast geography also opens up a unique arbitrage possibility. Tier 2 and Tier 3 doctors—whose patient load might be less intense—could field consults from urban patients in real time. The AI layer would handle most routine queries, so the expertise of a well-trained MBBS doctor, no matter their location, becomes instantly available to a patient in Mumbai or Delhi. In this scenario, the key differentiator is the quality of the AI engine, not necessarily the physical proximity of the doctor.
The reason this matters is that India isn’t just dealing with isolated issues – it’s facing a perfect storm of healthcare challenges that could catalyze a revolution in how healthcare is delivered. These pressures aren’t just problems to be solved; they’re the very forces that could drive the adoption of AI in healthcare at an unprecedented scale.
Making the “Uber for Healthcare” Business Case
Let me paint you a picture of what the future of healthcare in India could look like. Imagine an AI-driven app that serves as your first point of contact with the healthcare system. You’re feeling unwell, so you open the app and input (text, talk, or video chat) your symptoms. Maybe you take a photo of your rash or upload data from your smartwatch. The AI, trained on millions of cases, immediately starts its initial assessment.
But here’s where it gets interesting – this isn’t just another symptom checker. The AI is sophisticated enough to flag potential issues and suggest diagnostic tests as well as direct you to the closest service center, much like how Apna Vaidya helped with my cardiac situation. The real innovation, though, is what happens next: once it has a reasonable understanding of an individual’s situation, it would be routed to a network of MBBS doctors, each “on call” through the app itself, much like Uber drivers waiting for ride requests.
Recent studies back this up: a 2019 paper in the Indian Journal of Community Medicine found that well-designed direct-to-consumer
telemedicine programs significantly boosted patient satisfaction and reduced waiting times. Similarly, a 2021 McKinsey report estimates India’s digital health solutions—including AI triage—could grow at 35–40% annually, further validating the feasibility of an “Uber for healthcare” model.
These doctors, many of them recent graduates or early-career physicians, review the AI’s findings and either sign off on them or
escalate to a specialist (again in the network itself) if needed. Think about it: instead of seeing 100 patients in a crowded clinic for 2-3 minutes each, these doctors could thoughtfully review 30-50 AI-preprocessed cases daily, each from the comfort of their home or a small office.
The economics make compelling sense: Even with a modest consultation fee of ₹200 per patient (about $2.40), a doctor could earn ₹3,000-10,000 daily with a reasonable volume. That’s potentially more than what many earn in their early hospital jobs, and with better working conditions. More importantly, they’re leveraging their medical expertise more efficiently, focusing on medical decision-making rather than routine paperwork.
Beyond just AI triage and doctor consultations, the potential for expansion is enormous. Imagine tie-ups with national and regional diagnostic labs to offer on-demand home visits—much like Orange Health, but scaled across Tier 1, 2, and even rural regions. Pharmacy integration could also extend delivery beyond big cities. This isn’t trivial, but the first platform to coordinate diagnostics, medication fulfillment, and doctor validation seamlessly will reap enormous rewards.
For patients, the value proposition is equally clear. Instead of taking a day off work to visit a crowded clinic, they get near-instant medical advice. If they need tests, the app connects them with nearby diagnostic centers like Orange Health. If they need medication, it links to pharmacy delivery services. The entire healthcare journey becomes seamless, AI-guided, and doctor-validated.
The user interface would be crucial to making this work at scale. Imagine a Tinder-like interface for doctors – but instead of swiping left or right on potential dates, they’re rapidly reviewing AI-generated diagnoses and treatment plans. Swipe right to approve the AI’s assessment, swipe left to modify it, or swipe up to escalate to a specialist. Each interaction takes seconds, not minutes, with the AI learning from every doctor’s decision. The interface would be optimized for rapid medical decision-making while maintaining clinical rigor – think quick-tap standard modifications, voice-annotated corrections, and gesture-based common responses. This isn’t just about making things faster; it’s about making complex medical decisions more intuitive and efficient.
But here’s where it gets even more interesting: imagine this system evolving into a comprehensive healthcare platform. The app detects that you need a thyroid function test? One tap, and you’re connected to Orange Health for home sample collection. The AI and doctor recommend specific medications? They’re automatically queued up in your Tata 1mg cart for home delivery. Each service integration makes the platform more valuable and the healthcare journey more seamless.
Over time, this could evolve into something far more sophisticated. The AI could learn to predict when you might need your next HbA1c test based on your diabetes management patterns, automatically scheduling with your preferred diagnostic center. It could track medication adherence through pharmacy records and adjust recommendations accordingly. The system becomes not just reactive to health issues, but proactively engaged in maintaining wellness.
But the real magic lies in the data network effects. Each interaction teaches the AI, making it smarter. Each doctor’s decision helps refine the system’s triage capabilities. When doctors correct or modify the AI’s initial assessment, these adjustments are fed back into the system, continuously improving its accuracy. The doctor-in-the-loop model serves dual purposes: it ensures immediate quality control for patient care while simultaneously generating validated training data that makes the system more reliable. Over time, the platform will build an unprecedented database of healthcare patterns – how different communities present symptoms, how various conditions progress, what treatments work best. This creates a virtuous cycle where more usage leads to better accuracy, which in turn increases doctor confidence in the system. Unlike standalone AI systems that might miss crucial context or nuance, this human-AI collaboration combines the consistency and pattern recognition of AI with the experienced judgment of medical professionals.
Of course, there are tricky issues related to data security, clinical oversight, and regulatory compliance. Yet, these very challenges will distinguish the winning platform. In many ways, the first mover that deftly handles these complexities—while keeping the user experience smooth—will set the gold standard for AI-first healthcare in India. Also, remember India’s regulatory flexibility we discussed earlier? This creates space for thoughtful innovation while maintaining medical standards. Doctors would still make all final decisions, with the AI serving as an incredibly well-informed assistant. This reality is going to happen in the next few years in India. I’ve seen pieces of these things happening in various startups in India. The technology is ready. The doctors are willing. The patients are waiting. All we need is someone to put these pieces together in the right way. Honestly, Apna Vaidya could be the one that pushes things over the edge, but there are also a bunch of others who are gunning to make the same future a reality.
From Personal Experience to Dreaming Of “Uberified” Healthcare
When I first used AI to navigate my own health concerns in India – from that peculiar ECG reading to the thyroid issue – I wasn’t just experiencing the convenience of a flexible healthcare system. I was glimpsing the future of healthcare delivery. My ability to move seamlessly from AI recommendations to diagnostic tests, from digital reports to treatment decisions, wasn’t just a fortunate combination of circumstances – it was a preview of what healthcare could look like for millions of Indians.
India’s blend of an enormous patient base, flexible regulatory structures, cultural acceptance of out-of-pocket healthcare, and a growing pool of tech-savvy medical professionals makes it uniquely positioned for an AI-driven healthcare revolution. My personal experiences – seeing just how easy it is to order advanced tests and get AI-guided care – underscore how different this landscape is from most other countries.
While such a system raises important questions about medical ethics and patient care, the potential payoff could be transformative. An “Uber for healthcare” model, powered by AI triage and a network of doctors, could meet India’s urgent demand for accessible, efficient care – and ultimately reshape the entire healthcare sector. If done responsibly, the amount of real-world data generated would be unprecedented, fueling further research and improvement of AI tools.
Remember that doctor in Mumbai who was seeing 200 patients a day? Imagine if AI could help her focus on the 50 who truly needed her expertise while ensuring the other 150 still received quality care. Or that young MBBS graduate making less than an Uber driver? Picture them leveraging AI to build a thriving practice from their laptop. These aren’t just business opportunities; they’re chances to fundamentally improve healthcare delivery for over a billion people.
If you’re looking for the next big leap in AI-driven healthcare, keep your eyes on India. It may not just be a test bed – it could very well
be the launch pad. After all, my journey from a concerning ECG to an AI-guided diagnosis might soon be the standard experience for millions of Indians, not the exception.
Disclosure: I am an investor in Apna Vaidya and have helped guide its development, and I am also a co-founder of biostate.ai which has several healthcare initiatives in India. While this involvement obviously influences my perspective on the field and its future potential, it has also given me unique insights into both the challenges and opportunities in this space. My personal experiences, both as a user and as someone assisting (in a small form) to build these solutions, have only strengthened my conviction about India’s unique position to lead this healthcare transformation.