Healthcare AI Adoption Faces Critical Workforce Training Gap, 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 organizations worldwide. Based on insights from over 750 healthcare professionals including clinicians, IT leaders, and AI developers, the comprehensive study indicates that while AI implementation has become nearly universal, with 100% of surveyed organizations using AI in some form, 85% of clinicians feel they need additional training to use these technologies effectively in both patient care and operations.

Radixweb CEO Divyesh Patel noted that healthcare has clearly entered its AI-integrated phase, with technology no longer serving as the limiting factor. "What this report makes evident is that technology is no longer the limiting factor. Human readiness is," Patel stated. "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 introduces particular risk in environments where AI recommendations directly influence patient care decisions.

Despite these challenges, the report documents substantial progress in AI implementation. Approximately 50% of healthcare operations now use AI for efficiency-driven workflows including scheduling, revenue cycle management, documentation, and automation, with clinicians and IT leaders reporting noticeable improvements. The study found that 57% of clinicians report stronger clinical decision-making with AI assistance, while 43% observe early reductions in clinical errors from AI use. These findings indicate AI is moving beyond pilot testing to become an integral component of healthcare operations.

However, structural challenges beyond training continue to complicate AI adoption. According to 66% of healthcare IT leaders surveyed, fragmented legacy systems and complex regulatory environments limit AI's ability to move seamlessly across workflows. Integration challenges represent the most significant adoption hurdle identified in the research. Additionally, while organizations have noted early efficiency improvements, fewer than half (42%) have realized significant returns on their AI investments, highlighting a disconnect between investment timing and impact realization.

Radixweb COO Dharmesh Acharya emphasized that "AI maturity is rising faster than organizational maturity" in healthcare settings. "We're seeing strong adoption, but scaling responsibly requires more than deployment," Acharya explained. "It requires investment in skills, governance, and trust across clinical and IT teams." The report identifies 2026 as a crucial transition year from AI-assisted workflows to fully integrated AI systems, with future progress depending on workforce skills development, interoperable infrastructure, and governance models that ensure clinical trust alongside operational growth.

Technical development trends identified in the report show large language models leading healthcare AI development, with 60% of developers utilizing LLMs in their work. However, 57% of developers rank privacy and security as their top AI concern, indicating ongoing challenges in balancing innovation with patient data protection. The complete findings, including additional statistics and analysis, are available in the 2026 Global AI in Healthcare Report, which serves as a comprehensive playbook for HealthTech leaders navigating this evolving landscape.