Innovation to Impact: AI as a Public Health Gamechanger
Abstract
The round‑table examined how artificial intelligence (AI) can move from isolated innovation to large‑scale public‑health impact in India. Participants discussed policy levers, clinical adoption, public‑private partnerships, and concrete AI‑driven solutions that reduce costs, increase access, and improve outcomes. Perspectives from the Netherlands, the private sector, and the Indian government were woven together, culminating in a ministerial keynote that outlined national policy priorities, regulatory frameworks, and the launch of a new AI‑in‑healthcare strategy (SAHI).
Detailed Summary
The session opened with an informal remark (not attributed) about the importance of AI in making hospitals more efficient, reducing per‑patient costs, and scaling diagnostic throughput. The speaker highlighted that medical‑device manufacturers, especially Philips, are embedding AI to lower radiation exposure and increase the number of scans per day (e.g., from 20–25 to ~50 patients). The discussion positioned software‑as‑a‑medical‑device as an emerging growth area, with numerous Indian start‑ups poised to launch soon.
2. Netherlands Perspective – Enabling AI at Scale
Speaker: Mr. Nico Schiettekatte (Netherlands Embassy)
- Thanked Philips for hosting and noted the Netherlands’ co‑chair role (with Indonesia) in the AI for Economic Growth and Social Good working group.
- Described the 2019 national programme “Valuable AI in Healthcare.”
- Government‑led pilots, ethical AI guidelines, and the establishment of the WHO Collaborating Centre on AI Health Governance at TU Delft.
- Cited the October 2025 policy note titled “Realisation of AI in Healthcare,” shifting emphasis from experimentation to implementation and scaling.
- Outlined a two‑track approach: (i) stimulate AI‑driven innovation to address labour shortages and medical needs, and (ii) safeguard public values through legislation, notably the EU AI Act (risk‑based classification).
- Mentioned the EU “Apply AI” strategy reserving €1 billion to accelerate AI adoption, streamline market access for AI‑enabled medical devices, and support SME uptake.
Key Insight: A clear regulatory framework paired with dedicated funding accelerates responsible AI deployment.
3. Clinician Acceptance – Fortis Hospital’s Innovation Cell
Speaker: Dr. Bishnu Panigrahi (Fortis Healthcare)
- Reported the creation of a hospital‑wide Innovation Cell led by a senior doctor (administrator).
- Emphasised the patient journey: digital QR‑code check‑ins, chat‑bot triage, and AI‑enhanced imaging.
- Cited a “smart hospital” example in Singapore where AI reduces nursing workload (nurses currently spend 70 % of time on routine tasks).
- Highlighted AI’s role in insurance screening, radiology (early detection of lung cancer), and pre‑emptive care.
- Stressed that AI enables earlier diagnosis, reduces unnecessary procedures, and improves bedside efficiency.
Key Insight: Embedding AI within clinical workflows, especially to free nurses from repetitive tasks, yields tangible efficiency gains and better patient experiences.
4. Startup Ecosystem & National Success Stories – Mahajan Imaging & Labs
Speaker: Mr. Harsh Mahajan (Mahajan Imaging & Labs)
- Traced India’s AI milestones: 2018 Lancet paper on AI detection of brain haemorrhage from CT scans (work started 2015‑2017).
- Described the TB Programme: handheld X‑rays paired with AI triage have screened millions, flagging abnormal scans for follow‑up.
- Mentioned a thermal‑sensor bra for breast‑cancer screening that uses AI to prioritize women for mammography; still in validation phase.
- Asserted that ethical, supervised AI can dramatically upscale population‑level screening across TB, breast cancer, and other diseases.
- Forecasted a future where AI breaks silos (pathology, radiology, genomics, etc.) to deliver “pre‑digested” diagnoses at the point of care.
Key Insight: When integrated with existing public‑health programmes, AI can transform disease surveillance and early detection at massive scale.
5. Policy & Resource‑Constrained Environments – Views from Dr. V. K. Paul & Mr. Aman Sharma
Speaker: Dr. V. K. Paul (NITI Aayog) – (mostly referenced by other speakers; direct quotes limited).
Speaker: Mr. Aman Sharma (Joint Secretary, Dept. of Pharmaceuticals)
- Emphasised that AI must be embedded in public‑health workflows to realise impact.
- Identified three criteria for AI tools: fit‑for‑purpose, cost‑effectiveness, and triage capability (e.g., for TB, NCD follow‑up).
- Highlighted the Ayushman Bharat Digital Health Mission (ABDM) as the “gold‑standard” digital public‑health infrastructure, featuring open APIs for data sharing.
- Advocated designing AI for low‑resource settings, ensuring affordability of both software and hardware.
- Stressed the importance of front‑line worker usability: decision‑support systems should aid, not burden, health workers.
- Called for robust governance: continuous validation, human‑in‑the‑loop oversight, and ethical safeguards.
Key Insight: Scalable, frugal AI solutions tied to existing digital health platforms can act as force multipliers in resource‑constrained environments.
6. Panel Interaction – Cross‑Sector Dialogue
A brief exchange followed, summarising key points and probing each expert’s view:
- Nico reiterated the necessity of clear boundaries and ethical guidelines for AI’s success.
- Dr. Panigrahi reaffirmed that clinician trust is essential; AI’s adoption hinges on clinicians believing in its benefits.
- Mr. Mahajan highlighted the role of startups in delivering cost‑effective, AI‑driven diagnostics.
7. Closing Remarks – Invitation to Group Photograph
The moderator (unnamed) thanked the panel, invited Mr. Roy Jakobs (CEO, Philips) and Ms. Anupriya Patel (Minister) onto stage for a group photograph, and signalled the transition to the keynote address.
Keynote Address – Ms. Anupriya Patel (Minister of State for Health & Family Welfare, Ministry of Chemicals & Fertilizers)
8. Opening & Vision
- Acknowledged the India AI Impact Summit 2026 and the joint effort of government, industry, and academia.
- Cited Prime Minister Narendra Modi’s definition of AI as “all‑inclusive”, emphasizing health equity over algorithmic sophistication.
9. National AI‑in‑Health Strategy
- Announced the upcoming launch of SAHI (Strategy for AI in Healthcare for India) – a national guidance framework for states, regulators, and private players, scheduled for release 19 Feb during the summit.
- Noted India’s membership in the Health AI Global Regulatory Network, collaborating with the UK and Singapore on safety protocols.
10. Current AI Deployments in the Health Continuum
| Domain | AI Application | Impact |
|---|---|---|
| Disease Surveillance | Multilingual AI tool monitoring digital news in 13 languages | Real‑time outbreak alerts |
| One Health Mission | AI‑driven genome surveillance to predict zoonotic spill‑overs | Early warning for animal‑to‑human transmission |
| TB Elimination | Handheld X‑ray + AI triage; “Cough‑against‑TB” tool | 16 % extra case detection; 27 % reduction in adverse outcomes |
| Breast‑Cancer Screening | AI‑enabled thermal‑sensor bras (prototype) | Rapid risk stratification for mammography referral |
| Clinical Decision Support | AI‑assisted workflow integration across radiology, pathology, genomics | Breaking silos, delivering pre‑digested diagnoses |
11. Ecosystem Building
- Designated AI Centres of Excellence at premier institutions (AIIMS Delhi, AIIMS Rishikesh, PGI Chandigarh, etc.).
- Described a collaborative framework involving multiple ministries, ICMR, and private sector partners to co‑create clinically relevant, validated AI solutions.
12. Workforce Development & AI Literacy
- Announced a 20‑hour online training program on AI in healthcare, launched by the National Board of Examination & Medical Sciences, targeting doctors nationwide.
- Stressed that AI literacy is now a core competency for clinicians, especially in the Global South.
13. Ethical & Regulatory Safeguards
- Highlighted existing ethical guidelines issued by ICMR and ongoing work by SEDESCO (national regulator) to draft standards for AI‑enabled medical devices and software.
- Emphasised the principle that human operators remain accountable for AI decisions.
14. Closing Call to Action
- Urged participants to focus on scalable, frugal innovations, ensuring that AI solutions are inclusive, ethical, and aligned with national health priorities.
Closing Segment
- The moderator thanked the panelists and the minister, invited speakers to stay back for post‑session interaction, and formally concluded the session.
Key Takeaways
- AI as a cost‑reduction lever: Embedding AI into imaging equipment (e.g., Philips) can double patient throughput while cutting radiation exposure and operational costs.
- Regulatory clarity accelerates adoption: The EU AI Act and India’s emerging AI‑health policies (Realisation of AI in Healthcare, SAHI) provide risk‑based frameworks that foster responsible scaling.
- Clinician trust is pivotal: Successful AI roll‑out depends on clinicians believing in the technology; dedicated innovation cells and workflow‑centric design are essential.
- Start‑up ecosystem is booming: Indian start‑ups are ready to deliver AI‑driven diagnostics (brain‑hemorrhage detection, handheld X‑ray AI, thermal‑sensor breast‑cancer bra).
- Public‑health AI successes: AI‑enhanced TB screening and multilingual disease‑surveillance tools demonstrate measurable impact on case detection and outbreak monitoring.
- Frugal, low‑resource design: AI solutions must be affordable, hardware‑light, and operable by frontline workers without adding burdens.
- Human‑in‑the‑loop governance: Ethical guidelines, continuous validation, and clear accountability structures are non‑negotiable for sustained trust.
- National strategy (SAHI) imminent: A unified policy will guide AI integration across states, regulators, and private actors, aligning with global regulatory networks.
- AI literacy for clinicians: Mandatory AI training for doctors is being rolled out nationally to ensure a skilled workforce capable of leveraging AI tools.
- AI as an augmentative, not replacement, technology: AI can relieve clinicians of repetitive tasks, enabling focus on complex decision‑making and preserving the essential human touch in medicine.
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