Harvey is seeing a powerful network effect where enterprise clients demand their outside law firms purchase Harvey to collaborate more effectively. This creates a highly efficient, low-cost customer acquisition channel driven by the end customer.
Harvey AI's co-founder predicts AI will allow law firms to break the traditional billable-hour model. This shift will enable them to operate at a much larger scale with software-like margins, fundamentally changing the industry's structure and creating massive winners.
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.
Harvey's initial product was a tool for individual lawyers. The company found greater value by shifting focus to the productivity of entire legal teams and firms, tackling enterprise-level challenges like workflow orchestration, governance, and secure collaboration, which go far beyond simple model intelligence.
While law firms have an inherent conflict with AI due to the billable hour model, the push for adoption is coming from their clients. Corporations are now sending formal requests to their legal counsel, requiring them to use AI tools for efficiency and cost savings, thereby forcing the industry to adapt despite its traditional economic incentives.
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.
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.
John Morgan built the legal tech platform Litify for his own firm's needs. He then leveraged his massive case referral network by requiring partner firms to adopt Litify. This created a captive market for his software and streamlined his core business operations, establishing a powerful, self-reinforcing flywheel.
AI tools drastically reduce time for tasks traditionally billed by the hour. Clients, aware of these efficiencies, now demand law firms use AI and question hourly billing. This is forcing a non-optional industry shift towards alternative models like flat fees, driven by client pressure rather than firm strategy.
Harvey is building agentic AI for law by modeling it on the human workflow where a senior partner delegates a high-level task to a junior associate. The associate (or AI agent) then breaks it down, researches, drafts, and seeks feedback, with the entire client matter serving as the reinforcement learning environment.
Large companies integrate AI through three primary methods: buying third-party vendor solutions (e.g., Harvey for legal), building custom internal tools to improve efficiency, or embedding AI directly into their customer-facing products. Understanding these pathways is critical for any B2B AI startup's go-to-market strategy.