India's AI Diagnostics Moment: Scale, access, and the policy unlock
India's medical technology sector is moving fast. The market is valued near $14 billion today and is on track to approach $30 billion by 2030. With the right policy support, the country can set the pace for AI-driven diagnostics-bringing earlier detection, consistent quality, and lower cost to millions.
Fujifilm India's recent trajectory offers a practical view of how this can work at scale: strong growth, deeper Tier 2/3 penetration, and AI woven into everyday workflows-endoscopy, radiology, and population screening.
2025: Scale with measurable outcomes
The company reports sustained double-digit growth in healthcare, with CT and MRI as anchors in tertiary care and a standout year for endoscopy-30%+ year-on-year growth. Its installed base now exceeds 79,000 imaging systems across India, a large share placed in Tier 2 and Tier 3 cities. A nationwide service and training network is keeping uptime high and clinicians supported.
On infrastructure, Fujifilm opened a new corporate headquarters in Gurugram that also functions as a medical contact centre. On technology, solutions like the Synapse AI platform and CAD EYE have been deployed to assist early detection, reduce reading fatigue, and improve confidence at the point of care.
Public health impact is visible. In 2025, the team screened 125,000+ individuals for TB across 15 states and reached 100,000+ women through breast cancer awareness and screening efforts.
2026: Closer support, wider reach
The 2026 plan focuses on three levers: innovation, infrastructure, and partnerships. A new endoscopy service facility will strengthen after-sales support. "Make in India" evaluations are underway across multiple divisions to localize more of the stack.
Expect a push into Tier 2 and Tier 3 cities with AI-driven diagnostic platforms and personalized screening programs. Partnerships through NURA and collaborations with Indian technology firms will expand preventive care access and reduce diagnostic delays.
Tier 2 and Tier 3: Where access is won
Penetration beyond metros is no longer an ambition-it's the operating model. With tens of thousands of installations nationwide, Fujifilm cites Maharashtra, Karnataka, Kerala, and Uttar Pradesh as growth engines. Localized service models, fast repairs, and continuous training are proving as important as the hardware itself.
The next phase is clear: more AI-led screening centres and tighter integration with state health systems, private diagnostic chains, and NGOs to reach underserved districts consistently.
What's driving growth
Beyond CT and MRI adoption in tertiary care, portable imaging like the FDR Xair is seeing strong uptake across rural and urban settings. Endoscopy has been a bright spot, and AI-based tools such as CAD EYE grew at ~40%.
In FY24, healthcare revenue rose ~16% year-on-year. Expectations for FY25-26 remain positive, with double-digit growth guided by AI diagnostics, Tier 2/3 expansion, and scaled preventive programs.
How AI is changing day-to-day diagnostics
AI is making detection earlier and interpretation more consistent. In radiology, it flags subtle findings relevant to oncology and cardiovascular care, while automating measurements and triage to speed up workflows. In endoscopy, AI support has improved adenoma detection rates, helped characterize lesions, and prompted earlier cancer diagnoses.
Advanced CADx systems now predict lesion pathology, assist with identifying infections like Helicobacter pylori, and support treatment planning in conditions such as inflammatory bowel disease. For districts with few specialists, these tools help generalists and enable high-volume screening for TB, breast cancer, and liver disease.
Platforms like Synapse bring imaging, decision support, and workflow orchestration into one environment-so AI support shows up in the right moment, not as an extra step.
The roadblocks-and practical fixes
Three constraints continue to slow adoption: fragmented data, uneven digital infrastructure, and evolving regulations. Fujifilm's approach has been to localize solutions for Indian workflows, invest in clinician training, and build service depth to maintain uptime.
Tele-radiology programs for TB and advanced breast screening are scaling through government, NGO, and diagnostic chain partnerships. The company emphasizes ethical deployment, validation, and readiness to manufacture more locally as policies mature.
What policy can unlock a global hub
- Incentives that make local manufacturing viable across components, software, and consumables
- Streamlined, predictable regulatory pathways for AI-based devices and software
- Clear data governance with privacy, consent, and quality standards that enable research and clinical validation
- Investment in digital infrastructure across Tier 2/3 facilities to support imaging, storage, and telehealth
- Clinician upskilling programs so AI is used correctly and confidently at the point of care
These priorities align with national programs such as the Ayushman Bharat Digital Mission and PM-JAY. For details, see the official pages for the Ayushman Bharat Digital Mission and Ayushman Bharat - PM-JAY.
What providers and health systems can do next
- Set clear screening priorities for your catchment: TB, breast, cervical, liver, colorectal. Start with programs that have funding and follow-up capacity.
- Choose AI that proves clinical value: peer-reviewed evidence, local validation, and integration with your RIS/PACS and endoscopy systems.
- Build data discipline: standardized protocols, structured reports, and governance for annotation, audit, and feedback loops.
- Invest in skills: short, recurring training for clinicians and technicians. Track metrics like ADR, recall rates, and turnaround times.
- Design for uptime: preventive maintenance, remote support, and spare parts planning-especially outside metros.
- Leverage partnerships: state health departments, NGOs, and diagnostic networks to scale outreach and follow-up.
Upskilling teams on AI (optional but useful)
If your teams are building AI literacy for clinical workflows and data governance, curated learning tracks by role can help. Explore options by job function here: AI courses by job.
Bottom line
India has the patient volume, clinical talent, and enterprise momentum to lead in AI-driven diagnostics. With smart policy and disciplined execution-manufacturing incentives, clear regulation, data standards, stronger digital rails, and clinician training-the country can make advanced diagnostics accessible in every district and set a global benchmark for scale and quality.
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