Artificial intelligence (AI) has long been a source of hope, hype, and concern in healthcare. From IBM Watson's failed venture into the industry to the issues of algorithmic biases, AI has faced numerous challenges. A recent study led by researchers at Duke University highlights the chaotic reality of AI implementation in healthcare systems and hospitals. Drawing from the experiences of 89 professionals at 11 organizations, the study reveals the struggles and lessons learned from the rollouts of AI tools. One example of AI's potential success in healthcare is the recent study on ChatGPT (version 3.5), an AI chatbot found to outperform doctors in providing high-quality, empathetic answers to medical questions on the subreddit r/AskDocs. The study suggests that AI chat tools could help reduce physician burnout, improve patient adherence to medical guidance, and increase patient equity. However, there are several limitations and caveats to the study, such as the difference in questions people ask on Reddit versus in a doctor's office, and the quality of answers physicians offer on the internet compared to their own patients. The Duke University study identified an eight-point framework for implementing AI in healthcare systems. This involves identifying and prioritizing issues, exploring how AI could help, assessing outcomes, integrating the tool into existing workflows, validating the AI's safety and efficacy, rolling out the AI with communication and training, monitoring its performance, and updating or decommissioning the tool as needed. Addressing these challenges will be crucial for ensuring AI's successful adoption and effectiveness in healthcare.