You can't sue an AI model provider like Anthropic when an agent makes a costly mistake. Enterprises require a human-led organization, like a consulting firm, to take accountability and liability. This fundamental need for a "throat to choke" ensures the relevance of services firms in the AI era.

A crucial function for humans in an AI-driven economy is to serve as a target for lawsuits. Because you can't easily sue a data center, regulated professions will require a 'human in the loop' to take legal responsibility. This creates a valuable economic role for humans: being a legally accountable entity.

A Ninth Circuit ruling in Amazon vs. Perplexity established a key legal principle for agentic AI: the entity legally "accessing" a website is the user who deploys the agent, not the company that created it. This places liability on the end-user and has massive implications for AI-driven e-commerce and web interaction.

When an AI agent errs in a medical or financial context, it is legally unclear who is liable: the AI lab, the deploying company, or the end-user. This novel legal problem, which challenges a century of precedent, creates significant friction and will slow agent adoption in regulated industries.

As AI agents take over execution, the primary human role will evolve to setting constraints and shouldering the responsibility for agent decisions. Every employee will effectively become a manager of an AI team, with their main function being risk mitigation and accountability, turning everyone into a leader responsible for agent outcomes.

One of the most promising and neglected AI safety strategies is to create systems for making credible deals with AIs. Just as contracts prevent conflict in human society, offering AIs guaranteed resources in exchange for cooperation makes rebellion a less attractive option.

A significant portion of B2B contracts will soon be negotiated and executed by autonomous AI agents. This shift will create an entirely new class of disputes when agents err, necessitating automated, potentially on-chain, systems to resolve conflicts efficiently without human intervention.

While giving agents their own accounts seems like treating them as employees, the analogy breaks down with liability. A user is fully responsible for their agent's actions and requires complete oversight, unlike with a human employee. This creates a fundamental conflict for secure, autonomous collaboration.

AI agents could negotiate hyper-detailed contracts that account for every possible future eventuality, a theoretical concept currently impossible for humans. This would create a new standard for agreements by replacing legal default rules with bespoke, mutually-optimized terms.