Instead of selling software to traditional industries, a more defensible approach is to build vertically integrated companies. This involves acquiring or starting a business in a non-sexy industry (e.g., a law firm, hospital) and rebuilding its entire operational stack with AI at its core, something a pure software vendor cannot do.

The guest argues that a specific AI vertical is underinvested: automating administrative knowledge work that is fundamental to how companies get paid. These tools have high revenue durability as they become core financial infrastructure, yet receive less VC attention than other AI categories.

Historically, software did ~10% of the work (tracking, organizing). AI will invert this, with software actively performing 70-80% of tasks. This fundamental shift means customers will refuse to buy legacy software that doesn't do the majority of the work for them, massively expanding the total addressable market.

Thrive Holdings is executing an AI-driven "roll-up" strategy, committing $1 billion to acquire small accounting practices and create a single, AI-powered entity. Their AI has already cut tax prep time by a third. This is a blueprint for disrupting other fragmented, service-based industries.

Silicon Valley is biased towards open-ended knowledge work like software engineering. However, a larger, often ignored opportunity for AI lies in automating the repeatable, deterministic business processes that power most of the non-tech economy, from customer support to operations.

Traditional fund administrators often control access to a client's own financial data, forcing CFOs into a manual request process. This friction creates a significant opportunity for modern platforms that offer direct, real-time data access, turning a liability into a strategic asset for the fund.

Companies struggle to get value from AI because their data is fragmented across different systems (ERP, CRM, finance) with poor integrity. The primary challenge isn't the AI models themselves, but integrating these disparate data sets into a unified platform that agents can act upon.

The proliferation of SaaS tools forces thousands of employees to act as manual "human glue," moving data and connecting workflows between systems. The key value of AI agents is creating an intelligent layer to automate this mundane, connective work, freeing up employees for higher-value tasks.

Investment funds rely on manual processes and siloed data managed by fund admins. Hanover builds a central ERP to ingest all data (decks, emails, accounting). This allows partners to make critical decisions by directly querying their portfolio data via an LLM, bypassing slow, human-in-the-loop email requests to an admin.