Forcing businesses to pay a mandated high wage for a low-value job creates a powerful incentive to automate that role, especially with the rise of AI. A better approach is bottom-up regulation that fosters a competitive labor market, forcing companies to increase wages naturally to attract talent.

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.

Run HR, finance, and legal using AI agents that operate based on codified rules. This creates an autonomous back office where human intervention is only required for exceptions, not routine patterns. The mantra is: "patterns deserve code, exceptions deserve people."

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.

Historically, labor costs dwarfed software spending. As AI automates tasks, software budgets will balloon, turning into a primary corporate expense. This forces CFOs to scrutinize software ROI with the same rigor they once applied only to their workforce.

The primary challenge for direct-to-consumer (DTC) AI doctor services is not technology but economics. High customer acquisition costs and churn make a standalone subscription model untenable. Successful AI doctors will likely be a top-of-funnel feature for a larger, integrated healthcare business.

Instead of replacing experts, AI can reformat their advice. It can take a doctor's diagnosis and transform it into a digestible, day-by-day plan tailored to a user's specific goals and timeline, making complex medical guidance easier to follow.

Previously, building 'just a feature' was a flawed strategy. Now, an AI feature that replaces a human role (e.g., a receptionist) can command a high enough price to be a viable company wedge, even before it becomes a full product.

The proliferation of separate AI tools for providers (upcoding, auth requests) and payers (denials, downcoding) will lead to automated conflict. This friction could worsen administrative burdens rather than easing them, creating a high-speed, zero-sum game played by algorithms.