SHERRELL BENSON

My name is Sherrell Benson, and my work centers on the real-world deployment and scaling of artificial intelligence in healthcare systems. With a background in health informatics and clinical operations, I focus on identifying the enablers and barriers that affect AI implementation across experienced medical centers. While the promise of AI in diagnostics, patient monitoring, and operational optimization is well established, translating that promise into practice requires a deep understanding of workflows, infrastructure, and human factors within complex care environments. My research aims to bridge the gap between technological innovation and clinical adoption.

Drawing insights from leading academic hospitals and integrated health systems, I conduct qualitative and mixed-method studies to explore what makes AI deployment successful—or challenging. These include interviews with clinicians, IT leaders, compliance officers, and AI vendors, as well as case studies on AI-powered radiology tools, sepsis alerts, and clinical decision support systems. My research has shown that beyond algorithm performance, issues like change management, trust in automation, data quality, and integration into electronic health records (EHRs) play pivotal roles in determining long-term success. I aim to build evidence-based frameworks for AI readiness and maturity in healthcare institutions.

From my perspective working within experienced healthcare institutions, key factors influencing AI deployment include interdisciplinary collaboration, transparent governance models, clinical champion involvement, and ongoing performance auditing. Equally important are robust data infrastructures, vendor accountability, and institutional culture. I advocate for co-design approaches where clinicians and engineers collaboratively shape AI workflows to ensure they are intuitive, explainable, and clinically relevant. My work emphasizes the importance of aligning AI implementation with patient safety goals, regulatory compliance, and equitable care delivery.

Looking ahead, my vision is to support healthcare organizations in building sustainable, scalable AI ecosystems that enhance care without disrupting human-centered practice. I am currently developing an AI deployment maturity assessment tool and exploring models for cross-institutional learning networks that share best practices. My goal is to empower hospitals not only to adopt AI technologies but to evolve alongside them—establishing ethical, transparent, and data-driven infrastructures that adapt over time. Through collaborative research and translational insights, I hope to guide healthcare leaders through the complex landscape of AI integration.