Sunil Mittal: AI set to transform healthcare, education and research

Sunil Mittal: AI set to transform healthcare, education, and research

At the India AI Impact Summit, Bharti Group Chairman Sunil Mittal said AI has moved past trend status and is now a primary driver of change across industries. He pointed to healthcare, education, deep research, and medical sciences as areas ready for clear gains in efficiency, innovation, and access.

Within Bharti Group, AI already supports customer service, network planning, and operations. The focus is practical: better service quality and faster, smarter internal processes.

Mittal emphasized that impact won't stop at a couple of sectors. As organizations adopt AI, fresh opportunities will open across medical research and advanced scientific work.

What this means for healthcare leaders

AI is moving from pilots to daily workflows. The biggest wins show up in patient access, diagnostics support, care coordination, and back-office automation.

• Use clinical decision support as a second set of eyes; start with narrow, high-volume pathways like chest X-ray triage or sepsis alerts.
• Stand up AI-enabled patient access: symptom checkers, appointment routing, and follow-up reminders that cut wait times.
• Automate the revenue cycle and prior authorization to reduce denials and free up staff time.
• Build guardrails first: data governance, model validation on local populations, bias monitoring, and audit logs.

For practical how-tos and tools, see AI for Healthcare.

Implications for educators and learning teams

AI can personalize learning, lighten grading and planning, and expand support for learners who need it. The work is to pair these gains with clear policies and evidence.

• Run small course-level pilots: AI tutoring, automated feedback, and question generation with tight rubrics.
• Publish an AI use policy for students and staff covering academic integrity, data privacy, and accessibility.
• Invest in teacher upskilling and prompt libraries; measure impact with learning outcomes, not clicks.
• Ensure secure infrastructure and content filters; prefer tools with explainability and exportable data.

Explore proven approaches in AI for Education.

Deep research and scientific studies

AI shortens cycles for literature reviews, data cleaning, simulation, and lab automation. It also raises the bar on reproducibility and documentation.

• Adopt model and dataset cards, versioned pipelines, and pre-registration where it fits your study design.
• Plan compute and storage budgets early; align with institutional review and security standards.

Resources and case studies: AI for Science & Research.

Why the timing matters

The summit's scale reflects the momentum: over 300 curated exhibition pavilions and live demos, structured around People, Planet, and Progress. More than 600 startups are presenting population-scale solutions already running in real settings, with 500-plus sessions featuring thousands of speakers and panelists.

For professionals in healthcare and education, this is a window to assess working solutions, set standards, and partner with teams that can deliver measurable results this year.

Need guardrails to move safely? See the WHO guidance on AI in health and UNESCO's guidance on generative AI in education.