Healthcare AI Adoption Outpaces Workforce Training, Radixweb Report Finds

The 2026 Global AI in Healthcare Report from Radixweb reveals a significant disconnect between artificial intelligence adoption and workforce preparedness in healthcare settings. Based on insights from over 750 professionals worldwide, including clinicians, healthcare IT leaders, and AI developers, the report indicates that while 100% of surveyed healthcare organizations use AI in some capacity, 85% of healthcare professionals feel they need more training to use AI effectively in patient care and operations.

"Healthcare has clearly entered its AI-integrated phase," said Divyesh Patel, CEO of Radixweb. "What this report makes evident is that technology is no longer the limiting factor. Human readiness is. Clinicians recognize the value of AI, but without structured training and organizational support, that value cannot be fully realized." The report suggests this training gap creates particular risk in environments where AI recommendations directly influence patient care decisions.

Despite these challenges, the report documents substantial AI impact in healthcare operations. Fifty percent of healthcare operations use AI for efficiency-driven workflows such as scheduling, revenue cycle management, documentation, and automation, with both clinicians and IT leaders reporting noticeable improvements. The report shows 57% of clinicians report stronger clinical decision-making with AI, while 43% see early reductions in clinical errors from AI use.

However, structural barriers beyond training continue to hinder broader implementation. According to 66% of healthcare IT leaders, fragmented legacy systems and complex regulatory environments limit AI's ability to move seamlessly across workflows. Additionally, fewer than half (42%) of organizations have realized significant returns on their AI investments, highlighting a timing disconnect between implementation costs and measurable benefits.

"AI maturity is rising faster than organizational maturity," said Dharmesh Acharya, COO of Radixweb. "We're seeing strong adoption, but scaling responsibly requires more than deployment. It requires investment in skills, governance, and trust across clinical and IT teams." The report identifies large language models as leading healthcare AI development, used by 60% of developers, while 57% of developers rank privacy and security as their top AI concern.

The complete findings, including additional statistics and analysis, are available in the 2026 Global AI in Healthcare Report. The report positions 2026 as a crucial transition year from AI-assisted workflows to fully integrated systems, emphasizing that future progress depends on workforce skills, interoperable infrastructure, and governance models that ensure clinical trust alongside operational growth.