MeitY backs AI training platforms for clinicians; hospitals to host dedicated facilities
India is moving to make AI usable at the bedside, not just in pilots. The Ministry of Electronics and Information Technology (MeitY) is prioritising AI-based platforms to train healthcare professionals in clinical use. Plans include working with start-ups and setting up dedicated facilities in key hospitals to speed adoption, according to Sunita Verma, Scientist 'G' and Group Coordinator for the R&D Division at MeitY.
Speaking at the international symposium FRSM 2025 hosted by the All India Institute of Speech and Hearing (AIISH), Mysuru, Ms. Verma said the focus is clear: affordable, sustainable, indigenous, and inclusive health technologies. The hard part is cost-effectiveness, and that is where government, academia, and industry must align.
Event highlights
- MeitY to prioritise AI platforms that help clinicians use AI models effectively in practice.
- Dedicated AI facilities planned within select hospitals; start-up engagement to accelerate translation.
- IIT Dharwad Director calls for AI tools across diagnosis, assessment, and treatment in speech and hearing care.
What MeitY signalled
MeitY is building an ecosystem with the right policy push and funding so research converts into usable products. Ms. Verma urged FRSM 2025 delegates to identify a short list of priority problem statements that can be taken up nationally.
For healthcare leaders, this means future grants and programs will favour translational work, clear clinical outcomes, and measurable cost savings. It also points to more hospital-based testbeds where clinicians co-develop and validate tools.
Speech and hearing: ready use-cases
S.R.M. Prasanna, Director of IIIT Dharwad, underlined the immediate opportunity in communication disorders. He highlighted how AIISH clinicians and engineers can co-create tools that directly support diagnosis, assessment, and treatment.
A recent collaboration between IIT Guwahati and AIISH Mysuru has already produced automated tools to assess the severity of speech disorders. The expectation is simple: more such targeted projects that begin with clinical need and end with deployable tools.
About FRSM 2025
The two-day symposium "Frontiers of Research in Speech and Music (FRSM) 2025" focuses on the theme "Frontiers of AI Research in Speech Hearing Systems and Music Cognition." It is jointly organised by the Sir C.V. Raman Centre for Physics and Music, Jadavpur University, Kolkata, and the Centre for Rehabilitation Engineering, Acoustics and Biomedical Engineering (CRAB), AIISH, Mysuru.
This is the third time after 2007 and 2014 that AIISH has hosted the event. The symposium is partially funded by the Anusandhan National Research Foundation and MeitY, with participation from 97 researchers across 29 institutions including IITs, NITs, IIITs, universities, engineering and medical colleges, AIISH, and other speech and hearing institutes. Participants include speech and hearing professionals, musicologists, technologists, research scholars, scientists, and engineers.
Among the participants were Shankha Sanyal of Jadavpur University, Symposium Chairperson, and Ajish K. Abraham, Convener. P. Manjula, Director (in-charge), AIISH, presided over the event.
Why this matters for government and hospital leaders
- Training-first approach: Building clinician capability to use AI models safely and effectively is now a policy priority.
- Hospital-based facilities: Dedicated spaces signal a shift from lab prototypes to bedside deployment and monitoring.
- Cost discipline: Funding and scale-up will favour solutions with clear ROI and sustainable total cost of ownership.
Action checklist for immediate adoption
- Identify 3-5 clinical workflows where AI can reduce delays, improve triage, or standardise assessment (start with radiology, pathology, speech/hearing clinics).
- Set up a clinical AI working group with a named clinical lead, data lead, and biomedical engineering liaison.
- Pilot training cohorts for clinicians on model limitations, prompt strategies, validation, and escalation protocols.
- Co-develop with start-ups; require sandbox testing inside hospital data environments with strict audit trails.
- Run cost-effectiveness analyses alongside pilots (time saved, rework avoided, outcomes improved, cost per patient).
- Establish safety guardrails: bias testing across languages and accents, model drift monitoring, human-in-the-loop checkpoints.
- Adopt standard data governance and consent flows; prioritise multilingual datasets and interoperability with existing HIS/EMR.
Where collaboration can move fastest
- Speech and hearing: automated screening, severity scoring, therapy progress tracking, and low-resource language support.
- Triage and prioritisation: front-door symptom capture and routing for ENT, neurology, and rehabilitation clinics.
- Clinical documentation: structured notes and coding support to cut admin time without compromising accuracy.
Helpful resources
- Ministry of Electronics and Information Technology (MeitY)
- All India Institute of Speech and Hearing (AIISH)
- Curated AI courses by job role - for team upskilling and clinician onboarding
Bottom line
The policy signal is clear: train clinicians, build inside hospitals, and prove value. If your institution shortlists priority use-cases now and sets up a small, accountable pilot team, you will be ready to plug into the national programs as they scale.
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