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 study indicates that while 100% of surveyed healthcare organizations use AI in some form, 85% of healthcare professionals feel they need more training to use AI effectively in both 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 demonstrates that AI is delivering measurable impact, with 50% of healthcare operations using AI for efficiency-driven workflows such as scheduling, revenue cycle management, documentation, and automation. Despite this progress, the study uncovers structural friction beneath the surface. While clinicians increasingly rely on AI tools, the overwhelming majority still feel inadequately prepared. This skill gap introduces particular risk in environments where AI recommendations directly influence patient care. "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."
Beyond training challenges, the report identifies system integration and value realization as compounding obstacles to broader AI implementation. According to 66% of healthcare IT leaders, fragmented legacy systems and complex regulatory environments continue to limit AI's ability to move seamlessly across workflows. Additionally, while many organizations have noted early efficiency improvements, fewer than half (42%) have realized significant returns on their AI investments, highlighting a disconnect between the timing of investments and their impacts. The report provides detailed statistics showing both promise and challenges in current AI implementation. According to the findings, 57% of clinicians report stronger clinical decision-making with AI, and 43% see early reductions in clinical errors from AI use. However, 66% of healthcare IT leaders identify system integration as the biggest adoption hurdle, and 57% of developers rank privacy and security as their top AI concern. Large language models lead healthcare AI development, used by 60% of developers according to the study.
According to the report, 2026 is set to be a crucial year in the evolution of AI in healthcare, marking a transition from AI-assisted workflows to systems that are fully integrated with AI. The future of this progress hinges on workforce skills, interoperable infrastructure, and governance models that can ensure clinical trust alongside operational growth. The complete findings are available in the 2026 Global AI in Healthcare Report, which serves as a comprehensive resource for understanding current implementation challenges and opportunities.
