Healthcare leaders are under growing pressure to understand artificial intelligence, evaluate vendor claims, and decide where AI belongs in clinical, operational, and administrative workflows. But the challenge is no longer simply asking, "What can AI do?" The better question is: Can this AI tool be useful, safe, fair, secure, measurable, and accountable in our actual healthcare environment?
AI Decoded: A Healthcare Leader's Guide to Responsible AI Adoption is a practical, plain-language guide for executives, clinical leaders, administrators, digital health teams, and healthcare consultants who need to make better AI decisions without becoming data scientists.
Written by physician, healthcare executive, and technology consultant Temitayo Bewaji, MBBS, MBA, this book helps leaders move beyond hype and evaluate AI through the realities of healthcare delivery: data quality, workflow fit, clinical responsibility, patient trust, regulatory expectations, vendor risk, implementation readiness, and post-launch monitoring.
Inside, readers will learn how to:
- Understand AI, machine learning, deep learning, large language models, foundation models, RAG, and AI agents in practical healthcare terms
- Evaluate AI use cases across diagnosis, imaging, treatment planning, documentation, patient communication, revenue cycle, staffing, scheduling, resource planning, drug discovery, clinical trials, and real-world evidence
- Ask stronger questions before buying, piloting, or scaling AI tools
- Distinguish a model from a full AI system involving data, users, workflow, permissions, monitoring, and governance
- Assess evidence quality, including external validation, silent trials, prospective pilots, outcome studies, calibration, subgroup performance, and monitoring
- Build responsible governance structures using AI registers, model cards, risk reviews, approval gates, incident reporting, and retirement plans
- Manage legal, privacy, cybersecurity, regulatory, procurement, and compliance considerations
- Use practical templates for opportunity review, readiness assessment, project prioritization, vendor evaluation, pilot planning, ROI, monitoring, and board-level discussion
This book is designed for busy healthcare leaders who need clear decision support, not technical theory. It explains what matters, what to ask, what can go wrong, and how to move from interest in AI to responsible adoption.
Whether you are reviewing an AI-enabled vendor tool, preparing an AI governance framework, planning a pilot, briefing a board, or helping your organization decide where to start, AI Decoded gives you a structured way to think, question, prioritize, and act.
Healthcare AI is no longer just about choosing a model. It is about managing an AI-enabled system across its full lifecycle: data, workflow, people, safety, regulation, monitoring, and accountability.
