The Pulse
Three things shaping AI in healthcare this fortnight:
How AI is Being Used in Psychiatry: An APA Member Survey — Widespread concern about lack of AI training alongside cautious optimism highlights a field that sees potential but feels not yet fully prepared to implement it safely. (APA, 2026)
5 ways AI is reshaping the patient experience — Growing patient use of AI for health information and system-level adoption signals a shift in expectations around access, responsiveness, and digitally supported care. (Becker’s Hospital Review, 2026)
How to Safely Use AI for Diagnosis: 14 Recommendations from ECRI. — Rapid integration of AI into diagnostic workflows is outpacing governance, reinforcing the need for clear standards around safety, oversight, and transparency. (AHA, 2026)
Takeaway: AI is advancing quickly across care delivery, but its real impact will depend on how well training, trust, and clinical oversight keep pace with adoption.
Psychology & Behavioral Health
AI in the mental health care workforce is met with fear, pushback — and enthusiasm (NPR, 2026)
AI is being adopted rapidly in mental health settings, primarily for administrative and support functions rather than direct clinical care. At the same time, workforce tensions are emerging, with concerns about role displacement, safety, and the shift toward less specialized labor in some care processes. The field is moving toward a blended model where AI supports workflows, but clinicians remain central to diagnosis and treatment.
Clinician Cue: Focus on integrating AI into documentation and workflow support while advocating for clinician involvement in tool design and implementation.
Dipping Into ‘Rejection Therapy’ As A Self-Behavioral Resiliency Approach Via AI Guidance (Forbes, 2026)
The article presents rejection therapy as a structured way to build resilience, with AI acting as a guide to plan, execute, and reflect on exercises. It highlights how AI can help users address threat perception, avoidance, and catastrophic thinking through gradual exposure. However, it emphasizes that AI is not appropriate for serious conditions and raises concerns about accuracy and data privacy.
Clinician Cue: AI-guided behavioral exercises may be useful as adjunct tools for low-risk patients, but require clear boundaries, screening, and patient education.
Medicine & Clinical Innovation
Artificial intelligence in cardiovascular care: from promise to practice (European Commission, 2026)
AI is already demonstrating strong performance in cardiovascular imaging and stroke detection, matching specialist-level analysis and accelerating treatment decisions. With cardiovascular disease continuing to rise, these tools could help reduce preventable deaths if scaled effectively. The next phase will depend on building infrastructure, generating independent evidence, and aligning regulation to support safe deployment.
Quick Win: Track where AI is already matching specialist performance, and use those moments to re-affirm and support the role of clinical judgment, validation, and accountability around increasingly capable tools.
Chatbots are now prescribing psychiatric drugs (The Verge, 2026)
A new pilot program is testing whether AI chatbots can safely renew certain psychiatric medications under strict eligibility and monitoring conditions. The system includes safeguards such as patient screening, identity verification, and escalation protocols for risk factors. While it may improve access for stable patients, concerns remain about missed context and limitations in handling complex cases.
Quick Win: Maintain focus on patient safety, clear eligibility boundaries, and human oversight when evaluating emerging AI-supported care models.
Ethics & Oversight
Policy & Compliance: As AI expands into diagnostics and limited prescribing roles, maintaining clearly defined human oversight at each clinical decision point becomes essential.
Bias & Transparency: Patients and clinicians are increasingly relying on AI despite accuracy concerns, so make transparency around its use a routine part of care.
Accountability & Governance: With adoption outpacing governance in many settings, it becomes crucial to ground use in clear policies for consent, documentation, and accountability before scaling.
Wayde AI Insight
AI is settling into healthcare not as a breakthrough moment, but as a steady presence across workflows, decisions, and patient experiences. What stands out is not just what the technology can do, but how unevenly prepared the system is to absorb it. Clinicians are being asked to navigate tools that are advancing faster than training, policy, and shared norms. This creates a gap between capability and confidence that shows up in both skepticism and overreliance. The next phase of adoption will depend less on innovation and more on integration that feels clinically grounded, ethically sound, and aligned with real-world practice.
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Produced by Wayde AI with AI assistance.