Industries with historically low software adoption (like trial law or dentistry) are now viable markets. Instead of selling a tool, AI startups are selling an outcome—the automation of a specific labor role. This shifts the value proposition from a software expense to a direct labor cost replacement.

In regulated industries like finance, the primary barrier to full AI automation is often regulation, not just user trust. It is the technology provider's responsibility to prove AI's reliability and safety to regulators, much like the industry did to legitimize e-signatures over a decade ago.

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.

The immense regulatory complexity in U.S. healthcare creates an estimated $500 billion "tax" of administrative bloat. The non-obvious opportunity is that by using AI to eliminate this waste, the savings could be redirected to fund expanded patient care, rather than just being captured as profit.

Industries historically slow to adopt software are now rapidly embracing AI. Unlike rigid workflow tools, AI excels at parsing dense text and augmenting the nuanced, unstructured work common in these fields. This allows new AI vendors to gain traction without needing to rip-and-replace legacy systems of record like EHRs.

While AI has vast potential, its most immediate and successful entry point is automating prior authorizations. This administrative bottleneck is considered an 'easy win' because it's non-patient-facing, has a clear ROI, and sits at the front of treatment, leading to natural and rapid adoption.

AI adoption in drug companies isn't about moonshot discovery via a single prompt. Its immediate, high-impact use is in automating and error-proofing massive regulatory documents for the FDA, where a single misplaced comma can cause costly, multi-billion dollar delays.

The most significant immediate benefit AI can offer the public is halving healthcare costs. This can be achieved by automating primary care workflows, but it requires legislative innovation. Creating state-level 'AI sandboxes' would allow companies to safely prove out specific use cases and accelerate adoption.

AI tools can be rapidly deployed in areas like regulatory submissions and medical affairs because they augment human work on documents using public data, avoiding the need for massive IT infrastructure projects like data lakes.