AI in practice. Evidence over hype.
Practical guidance on AI strategy, workflow design and adoption, with leadership reflections and live venture concepts.
Turning an AI Rollout into Everyday Use
Design an adoption plan around real tasks, credible champions, protected practice time and measures that show whether the new workflow helps.
AI for Health Equity Requires Evidence and Oversight
Evaluate a specific barrier to care, distinguish administrative assistance from clinical decisions, and test who benefits, who is missed and who can seek help.
What Is Machine Learning? A Practical Buyer’s Guide
Choose between rules, predictive models and generative AI by testing the business task, data quality, cost and consequences of failure.