Helping Decode the New OS of Healthcare

I translate complex technological shifts into insights for curious minds.

I produce the BigTechMed research project, and am currently running an open source project involving cardiology data and LLM’s. If you are interested in China, AI, and healthcare, please download the pre-print of my working paper The Dragon In Healthcare.

Cleveland Clinic logo with a stylized four-square emblem and the words 'Cleveland Clinic'
California Medical Association logo featuring a stylized medical symbol in a rounded square and the organization's name.
Biogen logo with a blue and green abstract sphere beside the company name in blue text.
Novo Nordisk logo featuring a stylized blue bull and the company name.
Logo of Georgia Hospital Association with stylized peach outline.
Sentara logo with orange swirl and black text
Infirmary Health logo with text and lines
Financial Times logo in black text on a white background.
BBC logo with three black squares and white letters B, B, and C.
CNBC logo featuring a colorful peacock icon and black text.
Logo of the Greater New York Hospital Association with the acronym GNYHA and a caduceus symbol
The Wall Street Journal logo in black text on a white background.

Keynotes for 2026

AI & Patient Care

The Age Of Agentic: When Healthcare AI Stopped Listening and Started Doing

For years, healthcare AI was mostly about listening. Ambient scribes that transcribed notes. Chatbots that answered patient questions. AI that assisted but never acted. That era is over. The first six weeks of 2026 marked the most consequential shift in healthcare technology history: AI agents moved from "helpful assistant" to "autonomous worker." These are better chatbots, and they're systems that can plan, reason, and execute complex workflows without human intervention. We are moving from discrete tools to integrated digital colleagues. As these agents begin to handle high-stakes logic like referral management and pre-visit optimization, the industry may need to come to grips with a new reality of automated clinical and administrative throughput.

Key Takeaways

  • The jump from "copilot" to "colleague" happened faster than anyone expected—in just weeks
  • Healthcare organizations that were "pilot ready" are now finding themselves deployment ready
  • The economic argument shifted from "can AI help?" to "can we afford NOT to use AI agents?"
  • Vendors that were selling "AI assistants" are now racing to rebrand as "agent platforms"
  • ROI timelines have compressed from years to months.
Global Health Deployment

China’s AI Healthcare OS: Stress-Testing Innovation at Population Scale

China is executing a deliberate, state-orchestrated integration of AI into its national healthcare system to solve structural sustainability issues. From provincial mandates requiring AI diagnostic modules to the rapid deployment of medical LLMs in over 100 county hospitals, the focus has shifted from "technology as a tool" to "technology as an operating system." This session explores how a top-down approach is achieving a 30-45% reduction in physical visits while rewriting the rules of clinical validation and sovereign data control.

Key Takeaways

  • Baidu’s ERNIE-Med has already demonstrated a 41% reduction in unnecessary in-person visits in early provincial pilots.
  • Guangdong’s Q3 2025 mandate turns AI integration into a non-negotiable requirement for all new telemedicine platforms.
  • The NMPA’s accelerated review pathways prioritize modernization speed over exhaustive clinical validation hierarchies.
  • Large-scale platforms like Ping An Good Doctor are now routing 38% of first-contact consultations through AI triage engines.
  • Mandatory API integration into EHRs is creating a centralized infrastructure that addresses urban-rural access gaps at scale.

Available here as open resources April 10

Book cover titled 'Decoding I.T. Terms For Hospital Boards' with the subtitle 'Tech Terms For Trustees,' authored by Ron Galloway, with the phrase 'Clear & to the Point' at the top.
Book cover titled "Clear & To The Point: A Field Guide For Curious Minds" by Ron Galloway, with the subtitle "AI, Clear & To The Point" and mentioning the author as Director of Why Walmart Works.
Book cover titled "Clear & To The Point: Compounding Time with A.I. You, Multiplied" by Ron Galloway.

Everyone is talking about artificial intelligence, but few are explaining how to oversee it.

The existing literature tends to be either abstract theory or vendor-driven hype. What was missing was a clear, structured guide tailored to healthcare organizations. This report attempts to fill that gap.

AI governance may seem nebulous now, even intimidating. But it won’t remain optional.

Be it a clinical decision support tool, a patient-facing chatbot, or a system predicting readmissions, someone will be held accountable for what that tool does. Understanding this space is no longer a luxury. It’s a core duty of modern hospital leadership. Download the first 3 chapters here. Full edited book will be published soon.

Book cover titled "Clear & To The Point" with subtitle "Ethics, Oversight, Compliance, Strategy" and the large text "A.I. Governance For Hospitals" by Ron Galloway.

I have nearly 40 years of research experience to the intersection of technology and healthcare. A graduate of Georgia Tech, my background is institutional analysis, including tenure as a research analyst at Shearson/American Express and a decade at a quantitative RIA. In 2006, I founded the institutional research firm 818 Research LLC, which provides data and healthtech research to investment advisors.

My work in artificial Intelligence and machine learning spans 37 years, beginning with programming in Turbo Prolog at Shearson in my mid-20s. In addition to his research, I am the author of several books on technology and has produced three documentaries.

My work has been featured by global media outlets including The Wall Street Journal, The New York Times, CNN, CNBC, the BBC, and The Daily Show with Jon Stewart.