"Treat AI pilots as a proof of control, not a proof of intelligence." In our latest collaboration with Fueled, we explore why "open-ended" AI experiences in healthcare often create risk faster than they create value. From fabricated medical terms to hallucinated protocols, the stakes are too high for guesswork. To move forward responsibly, integrations must be observable, reversible, and auditable. This "three pillars: framing helps align leadership, from marketing to compliance, to ensure that AI experiences can be measured, traced, and corrected at scale. Check out the full white paper and webinar takeaways 👇
Following our recently published white paper providing a framework for AI adoption in healthcare, the head of our content solutions practice, Phil Crumm, joined Thierry Muller, VP of AI Products at WP Engine, and Tamara Bohlig, CMO at shared client Vida Health, for a follow-up webinar. The conversation surfaced and reinforced several practical lessons for healthcare teams exploring AI today: 👁️ AI needs to be observable, reversible, and auditable 🧱 Start with bounded use cases and a controlled knowledge base ⚖️ Design for a regulatory reality spanning HIPAA, FDA, state privacy laws, and GDPR 🧭 Personalization is powerful in healthcare, and can become risky fast when “anonymous” behavior data drifts into PHI territory We also shared a simple starter action plan: audit existing AI usage, build a safe sandbox with rollback, assess how the brand appears in AI search, and treat compliance as a partner early. https://lnkd.in/gVj5pyCx