Artificial intelligence is becoming deeply embedded in healthcare, transforming clinical, administrative, and operational workflows. As organizations contend with workforce shortages, rising costs, regulatory requirements, and sophisticated cyber threats, AI in healthcare offers opportunities to automate complex processes and improve decision-making. But realizing those benefits requires healthcare leaders to address an equally important priority: trust.
The Healthcare AI: Building Trust at Scale report explores how organizations can expand AI adoption while protecting sensitive data, maintaining compliance, and preserving patient safety.
Agentic AI Is Advancing Healthcare Automation
One emerging opportunity is agentic AI, which can reason, plan, and execute tasks across complex workflows rather than simply automate isolated actions. In healthcare, AI agents can support eligibility verification, compliance reviews, case management, document processing, reporting, and patient support.
The report also highlights AI evals, automated mechanisms that assess AI outputs for accuracy, completeness, safety, and regulatory alignment. When combined with human review, evals can help organizations accelerate decision-making without sacrificing accountability.
Healthcare Cybersecurity Shifts Toward Risk
Healthcare security teams face an expanding attack surface and an overwhelming number of vulnerabilities. Enhanced Cloud-Native Application Protection Platforms (CNAPPs) offer a more risk-based approach by correlating infrastructure, applications, identities, workloads, and sensitive data.
Instead of treating every vulnerability equally, organizations can identify attack pathways and prioritize remediation based on potential impact to patient records, clinical systems, and other critical assets.
Shadow AI Creates New Data Security Risks
As generative AI adoption accelerates, shadow AI—unauthorized or unmonitored use—is raising new concerns about PII, PHI, compliance, and patient trust.
The report emphasizes visibility and point-of-use monitoring rather than simply banning AI tools. Healthcare organizations can establish guardrails based on the user, tool, model, agent, and data involved, enabling responsible AI adoption while reducing the risk of sensitive information reaching unauthorized systems.
Making AI Governance an Enabler of Innovation
Successful healthcare AI strategies increasingly integrate innovation, security, and governance from the beginning. As autonomous AI agents become more capable, organizations must secure data, models, identities, endpoints, and agent activity within a continuous security environment.
Ultimately, healthcare AI governance and cybersecurity can enable innovation rather than restrict it. Access the Healthcare AI: Building Trust at Scale report to explore expert perspectives on building an AI strategy that improves efficiency while protecting compliance, security, and patient trust.
