AI Readiness In Healthcare, Without The Hype

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The pressure to “do AI” in healthcare is real, but shipping a model isn’t the same as changing care. With Dr. Saima Anis—physician turned public health leader and enterprise IT strategist—we unpack how hospitals can adopt agentic AI responsibly while actually making clinicians’ jobs easier. We start with the human questions a good diagnostician asks: where is the pain, who does it hurt, and what outcome matters? From there, we build the case for culture, literacy, and trust as the groundwork that makes any system stick.

We break down governance without the jargon: data lineage and quality, explainable models, stage-by-stage audits, and human override by design. Dr. Anis clarifies why agentic AI is not a chatbot or an RPA script; it’s a domain-trained, continuously learning framework that can draft notes, synthesize evidence, and propose structured differentials—if and only if it is integrated into real workflows with clear guardrails. We explore how to reduce cognitive burden for physicians, where to start with repetitive tasks, and how to prevent drift and hallucinations when agents collaborate.

Leaders will hear specific pitfalls from 2025 to avoid—vendor lock-in, FOMO-driven deployments, and loyalty to failing pilots—and practical habits to adopt in 2026: stakeholder alignment before tooling, measurable outcomes, and transparent audit trails. We also talk candidly about leading as a woman in a male-dominated field, sustaining momentum under pressure, and why innovation is not synonymous with AI but with creative problem solving that delivers value. If you’re planning a rollout or rescuing one, this conversation offers a pragmatic playbook to move from hype to helpful.

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