Electronic Health Record (EHR) companies have historically used proprietary formats to lock in customers. AI's ability to read and translate unstructured data from any source effectively breaks these data silos, finally making patient data truly portable.

The next evolution in personalized medicine will be interoperability between personal and clinical AIs. A patient's AI, rich with daily context, will interface with their doctor's AI, trained on clinical data, to create a shared understanding before the human consultation begins.

Unlike medical fields requiring physical procedures, psychiatry is fundamentally based on language, assessment, and analysis. This makes it uniquely suited for generative AI applications. Companies are now building fully AI-driven telehealth clinics that handle everything from patient evaluation to billing and clinical trial support.

The most significant opportunity for AI in healthcare lies not in optimizing existing software, but in automating 'net new' areas that once required human judgment. Functions like patient engagement, scheduling, and symptom triage are seeing explosive growth as AI steps into roles previously held only by staff.

Despite the hype, Datycs' CEO finds that even fine-tuned healthcare LLMs struggle with the real-world complexity and messiness of clinical notes. This reality check highlights the ongoing need for specialized NLP and domain-specific tools to achieve accuracy in healthcare.

A primary barrier to modernizing healthcare is that its core technology, the Electronic Health Record (EHR), is often built on archaic foundations from the 1960s-80s. This makes building modern user experiences incredibly difficult.

Current patient education relies on ineffective printouts. Generative AI can revolutionize this by creating personalized, interactive tools that adapt to a patient's specific health record, culture, language, and comprehension level.

An effective AI strategy in healthcare is not limited to consumer-facing assistants. A critical focus is building tools to augment the clinicians themselves. An AI 'assistant' for doctors to surface information and guide decisions scales expertise and improves care quality from the inside out.

An "AI arms race" is underway where stakeholders apply AI to broken, adversarial processes. The true transformation comes from reinventing these workflows entirely, such as moving to real-time payment adjudication where trust is pre-established, thus eliminating the core conflict that AI is currently used to fight over.