To penetrate tech-resistant markets like personal injury law, the winning model is not selling AI software but offering an AI-powered service. Finch acts as an outsourced, AI-augmented paralegal team, an easier value proposition for firms to adopt than training existing staff on new, complex tools.
Unlike traditional firms that bill by the hour, personal injury attorneys on contingency fees are highly motivated to adopt AI. Efficiency gains don't reduce billable hours; they directly boost profit margins by settling cases faster and with less manual work, creating clear and immediate ROI.
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.
Customers are hesitant to trust a black-box AI with critical operations. The winning business model is to sell a complete outcome or service, using AI internally for a massive efficiency advantage while keeping humans in the loop for quality and trust.
Contrary to its reputation for slow tech adoption, the legal industry is rapidly embracing advanced AI agents. The sheer volume of work and potential for efficiency gains are driving swift innovation, with firms even hiring lawyers specifically to help with AI product development.
VC Keith Rabois highlights a core conflict: law firms billing by the hour are disincentivized from adopting AI that makes associates more efficient, as it reduces revenue. This explains why corporate legal departments are faster adopters—their goal is to cut costs.
A new ecosystem is emerging where law firms are not just end-users of Harvey's AI but also channel partners. They are leveraging their expertise to help their in-house legal clients adopt and implement the technology, creating a new, high-margin line of business for themselves as tech consultants and implementers.
Instead of pursuing complex, open-ended consulting projects, partners can scale more effectively by creating productized, "turnkey AI" offerings for specific business units like legal or marketing. This approach lowers the adoption barrier for customers by delivering predictable results for a defined use case, making it easier to sell into departments or smaller businesses.
The future of technology sales, particularly AI, is not about selling infrastructure but about solving specific business problems. Partners must shift from a tech-centric pitch to a consultative approach, asking 'what keeps you up at night?' and re-engineering customer processes.
Thrive Capital invested in an AI-powered accounting firm, not an accounting AI software tool. Their thesis is that in some industries, the service provider who uses AI to become hyper-efficient will capture more value than software vendors selling tools to a fragmented customer base. This is a bet on the business model, not just the technology.
In a world where AI makes software cheap or free, the primary value shifts to specialized human expertise. Companies can monetize by using their software as a low-cost distribution channel to sell high-margin, high-ticket services that customers cannot easily replicate, like specialized security analysis.