2026 Is the Year of Governance

2025 was the year healthcare rushed to implement AI. 2026 is the year we find out who built the guardrails—and who did not. The velocity was staggering. In 2025, forty-seven states introduced over two hundred and fifty AI bills impacting healthcare. OpenAI launched ChatGPT Health, connecting medical records and wellness apps to 230 million weekly health queries. The EU AI Act entered full enforcement for general-purpose models. And ambient AI tools spread across health systems faster than the policies meant to govern them. The technology arrived. The oversight did not. THE IMPLEMENTATION GAP The problem was never whether AI could work in healthcare. The problem was whether organizations knew who should be watching it. Consider what happened at Sharp HealthCare. More than 100,000 patient encounters were allegedly recorded without proper consent using an ambient AI tool. The AI auto-populated consent language into the medical record, documenting that patients were advised and consented when they never did. This was not a technology failure. It was a governance failure. The system worked exactly as designed. No one had designed the oversight. The moment a medical record asserts consent that did not exist, this is no longer an innovation story. It is a record integrity crisis. THE REGULATORY MOMENTUM Regulators are catching up. And the convergence is accelerating. In the United States: Thirty-three AI healthcare bills were enacted across twenty-one states in 2025. Illinois prohibited AI from making independent therapeutic decisions or interacting directly with therapy clients. Texas now requires written disclosure to patients when AI is used in healthcare services. The FDA launched the TEMPO Pilot, requiring enhanced consent for AI-enabled devices in chronic care. In Europe: The EU AI Act is now fully in force for general-purpose models, with penalties reaching 15 million euros or 3% of global revenue. High-risk AI systems, including most medical devices, must comply by August 2026, with full implementation by August 2027. Healthcare AI is explicitly designated as high-risk, requiring conformity assessments, human oversight, and transparent documentation. Globally: The WHO continues to advance frameworks for AI governance in health. International standards bodies are aligning on requirements for transparency, auditability, and bias mitigation. The question is no longer whether regulation is coming. It is whether your organization will be ready when it arrives. THE 2030 DEADLINE The regulatory momentum is not just national. It is global. The World Health Organization has positioned AI governance as central to achieving Sustainable Development Goal 3: ensuring healthy lives and promoting well-being for all by 2030. The 2030 deadline is now four years away. Organizations that fail to build governance infrastructure in 2026 will not be positioned to meet it. This is not just about compliance. It is about whether AI narrows health disparities, or widens them.CHATGPT HEALTH: THE CONSUMER PRESSURE POINT On January 7, 2026, OpenAI launched ChatGPT Health, a dedicated experience allowing users to connect medical records and wellness apps to the chatbot. The scale is significant: over 230 million people globally ask health and wellness questions on ChatGPT every week. OpenAI built the product with physicians, developed clinical benchmarks, and created a separate data environment with enhanced privacy protections. They explicitly state that conversations in Health are not used to train foundation models. But here is the governance question no one is asking: When patients start bringing ChatGPT-generated summaries to their appointments, who is responsible for validating that information? When a patient says, "ChatGPT told me my lab results suggest X," what is the clinician's obligation? The consumer side of healthcare AI is now moving faster than the clinical side. And the governance implications are just beginning to surface. THE TRUST DEFICIT I spoke recently with Larry Kuhn, Psy.D., who has written extensively about the erosion of trust in human relationships. His point stayed with me: before we can figure out how to trust AI, we have to address the trust deficit we already have. The data confirms what many of us sense. According to Gallup, Americans' average confidence across major institutions has fallen to just 27%, the lowest point in nearly five decades of measurement. This is the context AI is entering. The technology inherits the credibility of the organization behind it. If your patients do not trust the health system, they will not trust the AI the health system deploys. Governance is not just about compliance. It is about earning the right to deploy these tools in the first place. WHAT GOVERNANCE ACTUALLY LOOKS LIKE The organizations that will lead in 2026 are not the ones that moved fastest. They are the ones that built the infrastructure to move confidently. That means: 1. Identifying who is qualified to provide oversight. Not every committee is equipped to govern AI. Clinical informatics, legal, compliance, and frontline clinicians must all have seats at the table with clear accountability for decisions. 2. Mapping AI systems before deploying them. You cannot govern what you cannot see. Organizations need inventories of every AI tool in use, including vendor-provided systems embedded in existing workflows. 3. Designing consent as a conversation, not a checkbox. The Sharp lawsuit revealed what happens when consent is automated. Meaningful consent requires transparency, clarity, and the genuine ability to refuse without friction. 4. Building auditability from the start. If a system suggests something that leads to a bad outcome, can you trace why it made that recommendation? If the answer is no, the system is not ready for deployment. 5. Aligning with emerging regulatory frameworks. The EU AI Act, state-level legislation, FDA guidance, and WHO standards are converging on common principles: transparency, human oversight, bias mitigation, and accountability. Organizations that align now will not have to retrofit later. THE COMPETITIVE DIFFERENTIATOR Here is the harder truth: governance is no longer a cost center. It is a competitive differentiator. The organizations that can demonstrate responsible AI deployment will earn patient trust. They will attract clinicians who want to work with tools they can understand and audit. They will avoid the litigation, regulatory scrutiny, and reputational damage that comes from moving too fast. 2025 was the year of experimentation. 2026 is the year of accountability. The question is not whether your organization is using AI. The question is whether your organization has built the governance to use it well.