AI-enabled systems, on the other hand, are designed for the era of AI. They are designed with the flexibility and scalability required to support AI applications. They are designed to handle large volumes of data, to integrate with other systems, and to adapt to the rapidly evolving landscape of AI. They are not just compatible with AI—they are built on it.

AI-enabled systems offer numerous advantages over legacy systems. They can aggregate and analyze data from various sources, enhancing the accuracy and reliability of AI predictions and recommendations. They can support interoperability, allowing for seamless data exchange between different systems and platforms. And they can adapt and evolve with the rapidly changing landscape of AI, ensuring that healthcare providers can continue to leverage the benefits of AI as it continues to advance.

The transition from legacy systems to AI-enabled systems is not just a technological shift—it's a cultural one. It requires healthcare organizations to embrace change, to abandon familiar but outdated systems, and to adopt new and unfamiliar ones. It requires them to recognize the limitations of legacy systems and the potential of AI-enabled systems. And most importantly, it requires them to put their trust in AI.

In my four decades in the healthcare IT industry, I've seen many changes. But the advent of AI is perhaps the most significant. AI has the potential to transform healthcare, to improve patient outcomes, to enhance operational efficiency, and to drive innovation. But to realize this potential, we need to abandon legacy systems and adopt AI-enabled systems.

In conclusion, the digital transformation of healthcare requires more than just the adoption of new technologies—it requires the abandonment of old ones. It requires a shift from legacy systems to AI-enabled systems. And as we navigate the complexities of modern healthcare, this shift is not just an option—it's a necessity.