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There's an irony in AI companies, which claim their tech will automate professional services, hiring multiple law firms and bankers for their IPOs. Their reliance on traditional services for such critical functions undermines their own disruption narrative and suggests the promised automation is still far from reality.

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When auditing firm KPMG tried to pay its own auditors less by claiming AI can automate their work, it sent a disastrous public signal. By arguing for the commoditization of its core service, KPMG accidentally announced to the world that its own business model is under direct threat from automation.

As a side hustle, lawyers are now working for data-labeling companies to train AI models on legal tasks. While they see it as being 'part of the change,' they are directly contributing to building the technology that could automate and devalue the very expertise they possess, potentially cannibalizing their future work.

The traditional law firm model relies on a large base of junior associates for grunt work. As AI automates these tasks, the need for a large entry-level class shrinks, while mid-career lawyers who can effectively leverage AI become more valuable, morphing the firm's structure into a diamond shape.

Despite the potential for AI to create more efficient legal services, new tech-first law firms face significant hurdles. The established reputation of a major law firm ("the name on the letterhead") sends a powerful signal in litigation. Furthermore, incumbent firms carry malpractice insurance, meaning they assume liability for mistakes—a crucial function AI startups cannot easily replicate.

Contrary to long-held predictions, AI is disrupting high-status, cognitive professions like law and software engineering before manual labor jobs. This surprising reversal upends the perceived value of higher education and traditional career paths, as the jobs requiring expensive degrees are among the first to be threatened by automation.

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.

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.

The fear that AI will eliminate jobs in fields like law is misplaced. While it automates low-level tasks, it also enables clients to grow faster and create more complex products. This generates a new wave of demand for high-level advisory on emerging issues like AI risk and global regulations.

Contrary to fears of mass unemployment, AI's biggest losers will likely be the upper-middle class. The traditionally secure, high-paying career paths in consulting and law are highly susceptible to AI disruption, while other socioeconomic groups may see more benefits.

While AI is expected to automate routine knowledge work, the hourly rates for elite lawyers are soaring to previously unthinkable levels like $3,400. This indicates that high-stakes, specialized legal work—crisis management, Supreme Court arguments, and complex deal-making—is becoming more valuable and less susceptible to automation.