AI enables "software does labor" business models in industries previously deemed too small for specialized software, like dental offices or trial law. By replacing or augmenting specific labor tasks, startups can justify high-value contracts in markets that historically wouldn't pay for traditional SaaS tools.

Mala Gaonkar argues the most profound applications of AI are improving non-tech industries. For example, AI has improved the accuracy and speed of medical scans by 70% and is transforming the 300 million surgeries performed globally each year through robotics, reducing errors.

The startup playbook demanded huge markets to support large, expensive teams funded by VCs. Since AI development tools shrink team size and capital needs, founders can now build sustainable businesses by solving problems for smaller, previously unviable niche audiences.

Healthcare has historically been a service, with costs tied to licensed professionals. AI models like Gemini and ChatGPT are changing this by providing medical advice, effectively turning healthcare into a product. This shift, currently tolerated by regulators, could dramatically lower costs and increase access, just like software products.

VCs have traditionally ignored the massive $16T services sector due to its low margins. AI automation can fundamentally change this by eliminating repetitive tasks, allowing these companies to achieve margin profiles similar to software businesses, thus making the sector newly viable for venture investment.

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.

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.

The $1.8B telehealth company MedV is described as an "AI-enabled wrapper" not for a foundation model, but for the GLP-1 drug industry. This insight reframes the "wrapper" concept: AI's greatest immediate impact may be creating hyper-efficient operational layers over existing industries like telehealth, not just building on top of LLMs.

Businesses previously considered non-venture scale due to service-based models and low margins, like Managed Service Providers (MSPs), are becoming investable. By building with an AI-first core, these companies can achieve the high margins and scalability required for venture returns, blurring the line between service and product.