Why Health Systems Are Betting on AI That Fits the Workflow — Not the Other Way Around
Health system leaders have spent the last two years hearing the same pitch from every AI vendor: this tool will transform your operations. What many have learned instead is that the AI investments actually delivering value are the ones nobody notices — because they don't ask clinicians, revenue cycle teams, or executives to change how they already work.
That throughline is showing up across health system AI strategy right now: an investment approach built less around chasing capability and more around protecting capacity — clinical, operational, and capital.
Preserving Patient Safety with Healthcare IT/Part 3 - Preventing the IT Snowball Effect with Insufficient AI Governance
Patient safety is the core promise every healthcare organization makes to its community. In a world of EHR modernization, cloud migrations, and aggressive AI adoption, that promise now depends as much on healthcare IT and governance as it does on bedside care. As AI-driven tools move from pilots to production—supporting triage, diagnostics, documentation, and operational decisions—the uncomfortable truth is that governance has not kept pace with innovation. That gap is now a direct patient safety risk, not just a technology risk.
Navigating Technology Headwinds - Current State of AI & Regulatory Compliance in Healthcare
The current state of AI and healthcare regulation is defined by rapid clinical adoption, a surge of new rules, and a shift from experimental pilots to tightly governed, “trustworthy” systems integrated into existing medical‑device law. To ensure patient safety, additional AI‑specific safeguards are needed around transparency, lifecycle management, data governance and data security.