The Pulse
Three things shaping AI in healthcare this fortnight:
Augmented intelligence in medicine — With more than 80% of physicians now reporting professional AI use, the AMA is pushing a stronger message that AI should support clinicians, not replace judgment, and that governance and accountability need to keep pace with adoption. (AMA, 2026)
Trump calls off AI executive order over concern it could weaken US tech edge — The White House pulled back a proposed AI safety order tied to national security reviews, highlighting the growing tension between AI oversight and fears of slowing U.S. competitiveness. (AP, 2026)
Illinois Lawmakers Just Passed America’s Strongest AI Safety Bill — Illinois is moving beyond voluntary AI safety reporting by requiring third-party audits of frontier AI companies, signaling that states may begin taking a larger role in AI accountability and oversight. (Wired, 2026)
Takeaway: AI adoption, regulation, and governance are all accelerating at once, leaving healthcare organizations under increasing pressure to balance innovation with accountability and trust.
Psychology & Behavioral Health
Therapists are using AI to take notes. Is it a useful tool or a breach of trust? (NPR, 2026)
AI note-taking tools are gaining traction in therapy because they can significantly reduce documentation time and administrative burden for clinicians. At the same time, the article highlights growing concerns that recording sessions and using AI-generated summaries may affect trust, privacy, and a client’s willingness to speak openly. The strongest message is that consent, transparency, and clinician review are essential before AI-generated notes become part of the clinical record.
Clinician Cue: If AI note-taking is used, clients should clearly understand what is being recorded, how it is processed, and who remains accountable for the final documentation.
Researchers developed an AI model that used routine electronic health record data to predict adult ADHD months before formal diagnosis with relatively strong accuracy. The system identified patterns linked to substance use, stimulant use, caffeine-related indicators, and some birth-related complications as potential early signals. Researchers emphasized that the tool is intended to support earlier identification and referral, not replace clinician evaluation or diagnosis.
Clinician Cue: Predictive AI may help surface overlooked patterns earlier, but diagnosis still requires clinical context, assessment, and human judgment.
Medicine & Clinical Innovation
Governor Newsom signs first-of-its-kind executive order to prepare workers and businesses for potential AI disruption (Gov.Ca, 2026)
California’s executive order signals that AI is now being treated as a workforce and economic transition issue, not only a technology issue. The policy focuses on collecting labor-impact data, preparing workers through training, and helping organizations respond to disruption before it becomes a larger operational problem. For healthcare and behavioral health leaders, the order reinforces that AI adoption requires workforce planning, governance, and change management alongside implementation.
Quick Win: Start identifying which workflows may change most with AI adoption and pair technology planning with staff education and transition support early.
ASCO 2026: New AI Tool May Help Personalize Multiple Myeloma Treatment (NewsWise, 2026)
Researchers used AI to analyze routine bone marrow biopsy slides and identify immune patterns that may predict which multiple myeloma treatments are most effective for certain patients. The study found major outcome differences between treatment approaches in some AI-identified patient groups, suggesting a future path toward more personalized treatment decisions. Researchers cautioned that the tool remains investigational and still requires prospective validation before clinical use.
Quick Win: AI-driven personalization tools are moving closer to real clinical decision support, which means healthcare organizations should start preparing for how predictive AI may help tailor treatments and improve patient care in the future.
Ethics & Oversight
Policy & Compliance: Illinois passed a major AI safety bill requiring third-party audits of frontier AI systems, while federal debates continue around how much oversight AI companies should face.
Bias & Transparency: New AI tools in mental health and medicine are showing predictive promise, but researchers continue stressing that these systems are support tools, not replacements for clinical judgment.
Accountability & Governance: As AI becomes more common in documentation and treatment support, clear consent, transparency, and human review are becoming central expectations for responsible use.
Wayde AI Insight
This edition reflects a broader shift happening across healthcare and behavioral health. AI is moving beyond experimentation and becoming part of routine clinical, operational, and policy conversations. At the same time, laws and oversight efforts are evolving quickly at both the state and federal level, with policymakers debating how to balance innovation, safety, accountability, and competitiveness. Nearly every story points back to the same issue: trust. Whether the topic is therapy notes, predictive diagnosis tools, workforce disruption, or personalized cancer treatment, the central question is no longer whether AI can assist healthcare. It is how to integrate these tools responsibly while keeping accountability, transparency, and human judgment firmly in place.
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Produced by Wayde AI with AI assistance.