Hospitals to step up AI spending despite deployment hurdles: CII-PwC

While 64 per cent of healthcare leaders surveyed have piloted AI applications, only 11 per cent have moved them into production, with data quality the biggest hurdle

Indian hospitals are likely to increase spending on artificial intelligence over the next two years despite most healthcare organisations struggling to move AI applications from pilots to full-scale production, according to a CII-PwC report.

 

The report, released on the sidelines of the CII Hospital Tech 2026 event, based on a survey of 28 senior healthcare leaders conducted in August, found that 93 per cent of respondents believe AI can drive efficiencies, while 64 per cent have already piloted AI applications. However, only 11 per cent have taken AI into production, highlighting the gap between industry interest and actual deployment.

 

The report said funding is not the primary barrier to AI adoption. Only 7 per cent of respondents identified budget constraints as the biggest reason for AI deployments stalling. Instead, data quality emerged as the biggest hurdle, cited by 36 per cent, followed by change management at 21 per cent and clinician adoption at 14 per cent.

 

 

Healthcare organisations are currently evaluating AI across functions ranging from patient chatbots and remote monitoring to imaging, clinical decision support, finance, claims and supply-chain management. Imaging and diagnostic AI and clinical decision-support tools have attracted relatively higher levels of piloting, but their conversion into production use remains limited.

 

The report identified data platforms, AI governance and talent as key foundations for scaling AI in hospitals. It cautioned that a successful pilot does not necessarily translate into production success, with hospitals needing to establish measurable outcomes, full-scale costs and clear ownership before deploying AI across workflows.

 

The report said AI could help address some of India's structural healthcare constraints by extending specialist expertise to underserved areas, reducing the administrative burden on clinical staff and improving utilisation of existing hospital infrastructure. Use cases include automated documentation, scheduling, discharge planning, predictive alerts and remote monitoring.

 

The survey covered 23 healthcare providers, three medtech companies, one diagnostics company and one dialysis organisation, with CEOs/managing directors accounting for half of the respondents.