India’s healthcare system faces a critical challenge, balancing immense demand from a growing population with significant gaps in infrastructure and access.The sector is rapidly shifting towards digital-first solutions to enhance efficiency and meet consumer expectations. “Agentic AI is emerging as a powerful accelerator helping payers, providers and public health systems deliver more accessible, efficient, and inclusive care,” says Venky Ananth, EVP & global head of healthcare, Infosys. In this interview with Sudhir Chowdhary, Ananth shares his perspective on how AI-enabled tools can reduce clinical workload and support faster, more accurate decision-making. Excerpts::
How is Infosys deploying agentic AI across its healthcare solutions today?
Infosys integrates agentic AI across our healthcare portfolio to automate complex, multi-step workflows while keeping clinicians and administrators firmly in control. Through platforms like Infosys Topaz fabric, we combine large language models with governed decision frameworks to create AI agents that can benefits information, help prior-authorization, orchestrate care-coordination steps, and proactively surface gaps in care. These agentic capabilities operate within strict guardrails, ensuring traceability, auditability, and safety.
We are also embedding AI agents into population health, revenue cycle, and member-service operations to reduce administrative burden and enable faster, more accurate responses. The priority is not automation for its own sake, but intelligent delegation that preserves quality and expands access to care.
How do autonomous systems reduce clinician workload?
Agentic AI reduces clinician workload by taking on high-volume, low-value tasks that erode face-to-face care time. Examples include auto-drafting encounter summaries, pre-populating orders based on clinical context, triaging inbox messages, and retrieving relevant guidelines during consultations.
Crucially, these AI agents operate under human-validated protocols and never make unsupervised clinical decisions. Infosys ensures all outputs are explainable, transparent, and traceable to source data, allowing clinicians to verify accuracy quickly. By reducing administrative friction, clinicians gain more cognitive capacity for complex cases and meaningful patient interaction. This improves quality, reduces burnout, and supports safer, more timely decision-making, helping health systems deliver high-quality care without overwhelming their workforce.
How are your AI-led solutions benefiting the healthcare system?
We see strong value in three domains: care delivery, payer operations, and public-health outreach. Health systems are using agentic AI to streamline pre-visit preparation, accelerate clinical documentation, and improve discharge coordination, reducing average processing times by 25-40% in early deployments.
Payers are applying AI agents to claims routing, member-service summarisation, and prior-authorisation review, achieving faster turnaround and more personalised interactions. Public-health agencies are using AI-enabled analytics to identify underserved populations and target interventions more precisely, improving health-equity outcomes.
Across these examples, the impact is consistent: better efficiency, faster access to services, and a markedly improved patient or member experience driven by intelligent, well-governed automation.
Healthcare needs data interoperability more than ever…
Interoperability is foundational to safe and effective agentic AI. Infosys uses a standards-first approach grounded in fast healthcare interoperability resources (FHIR) APIs, zero-trust security principles, and rigorous data-governance frameworks. Infosys Topaz fabric provides a cloud-agnostic data fabric that unifies clinical, operational, and claims information without forcing systems into a single platform.
We leverage privacy-preserving techniques such as tokenisation, differential access controls, and audit trails to ensure data is usable for AI while remaining protected. Our integration accelerators allow disparate systems, and public-health databases to communicate securely, reducing fragmentation that disproportionately affects vulnerable populations. The result is a trusted, compliant, and scalable foundation for AI-driven transformation across the ecosystem.
Looking ahead, how is Infosys evolving its healthcare portfolio?
Our strategic focus is on building a connected, anticipatory health ecosystem where AI, automation, and interoperability converge to deliver more proactive, personalised, and equitable care.
Equally important is responsible AI: robust governance, transparent model behavior, and continuous risk monitoring. By aligning technology, trust, and human-centered design, we aim to help health systems move from reactive treatment to proactive, connected, digital-first care that reaches everyone.