Technology and rising investments are creating an optimistic environment for India's health tech sector, leading to its growth. In 2024, it was valued at $6.5 billion, and by 2033, it is projected to hit $78.3 billion, growing at 28.67 per cent annually, according to Custom Market Insights. Agentic AI has taken over this change, integrating intelligent automation into clinical and administrative workflows to make healthcare more efficient. Shitiz Ruhail, Co-Founder & Chief Growth Officer, Digital Darwin reveals more
Hospitals are adopting AI agents to simplify operations, cut costs, and improve patient care. Unlike basic automation tools, these AI systems not only follow commands—they have cognitive capabilities and learn from data, adapt to real-world situations, and provide insights that drive better decision-making. By integrating with hospital management systems, electronic health records, and customer service platforms, AI agents help eliminate inefficiencies, improve accuracy, and speed up processes.
One example is AgenticAI-powered scheduling systems, which help hospitals manage appointments more effectively. These tools interact with patients through multiple communication channels like phone calls, chat texts etc, making it easier to book appointments, send reminders, and provide real-time updates on availability. This leads to shorter wait times, fewer no-shows, and better resource utilisation, ultimately increasing hospital revenue without adding to operational stress.
AI in Clinical Documentation and Medical Coding
As per the Draft NABH recommendations 2024, all health records including diagnosis, morbidity and mortality should be coded with ICD 10/11 or SNOMED CT. AI-driven tools can assist doctors and nurses by transcribing and organising clinical notes, reducing paperwork and allowing them to focus more on patient care. In medical coding, AI ensures accuracy by automatically converting clinical notes into standardized codes like ICD and SNOMED CT, improving billing efficiency and insurance claim processing.
Traditionally, medical coding has been a labour-intensive process prone to errors. With AI automation, hospitals can process billing faster, reduce mistakes, and speed up reimbursements. AI also helps detect discrepancies in coding, ensuring compliance with regulations and preventing revenue losses.
AI-Driven Patient Engagement and Follow-ups
In a country where 70 per cent of the population lacks adequate healthcare access, keeping patients engaged is a major challenge. AI-powered virtual assistants with multilingual support can provide ongoing healthcare support, from sending reminders for follow-up visits to offering personalized recovery guidance.
For patients with chronic conditions and the elderly, AI agents play a critical role in monitoring health trends and alerting doctors to potential issues before they become serious. This early intervention not only improves patient outcomes but also reduces hospital readmissions, making healthcare more sustainable in the long run.
Improving Financial Stability and Resource Management
Hospitals rely on both quality care and operational efficiency to stay financially stable. AgenticAI-powered analytics help administrators make smarter decisions about staffing, budgeting, and resource allocation. By analysing market trends and financial data, AI tools identify new revenue opportunities while keeping costs under control.
For instance, AI automates insurance verification and claims processing, reducing delays and minimising claim denials. This means hospitals can secure reimbursements faster while focusing on delivering better patient care. Additionally, AI-driven planning tools help hospital executives track industry trends and fine-tune their business strategies.
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In 2023, healthtech attracted $7 billion of India’s $30 billion healthcare innovation market. By 2028, it could double to $21 billion, capturing 35% of the market.
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Strengthening Data Security and Compliance
As AI becomes more common in healthcare, ensuring data security and compliance with regulations is critical. AI-driven healthcare systems come with built-in security frameworks that meet standards like HIPAA, PDP, GDPR, and SOC 2. These platforms also use explainable AI, making sure every decision is transparent and backed by clear reasoning.
To improve reliability and avoid misleading recommendations, AI models are trained using verified medical datasets. This ensures AI-driven insights align with clinical best practices, maintaining high standards of patient care and trust. Moreover, AI is being designed with built-in empathy, ensuring interactions remain supportive and patient-focussed.
