Previously, disputing a small charge or arguing for a refund was not worth the time. Now, consumers and businesses can deploy AI agents to handle these negotiations endlessly and for free. This shift will force companies to re-evaluate policies around chargebacks and customer disputes.

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Litigation is costly because it's an arms race to explore a vast combinatorial space of legal arguments. Sufficiently powerful and cheap AI could search this space so exhaustively that no useful new moves remain, effectively ending the arms race and placing a natural ceiling on legal costs.

In categories like customer support, where AI can handle the vast majority of queries, charging per human agent ('per seat') no longer makes sense. The business model is shifting to be outcome-based, where customers pay for the value delivered, such as per ticket resolved or per successful interaction.

Insurers use AI to auto-deny claims and require tedious phone calls for appeals. Lunabill provides hospitals with an AI voice bot to automate these calls. This creates an arms race where one company's AI will inevitably negotiate with another's, foreshadowing a future where many adversarial B2B processes become fully automated AI-to-AI interactions.

As consumers use AI to analyze contracts and diagnose problems, sellers will deploy their own AI counter-tools. This will escalate negotiations from a battle between people to a battle between bots, potentially requiring third-party AI arbitrators to resolve disputes.

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.

Traditional software automated standardized processes but struggled with complex human interactions like call center support. Generative AI's ability to understand natural language allows software to automate these nuanced tasks, dramatically expanding the total addressable market by tackling problems that were previously impossible to solve with code.

The credit repair industry is notoriously scammy and difficult for consumers to navigate. An AI-powered ChatGPT app could provide a transparent, automated alternative by connecting to credit bureaus, offering dispute templates, and simulating score improvements. This model can be applied to other opaque consumer service industries.

Amazon is suing Perplexity because its AI agent can autonomously log into user accounts and make purchases. This isn't just a legal spat over terms of service; it's the first major corporate conflict over AI agent-driven commerce, foreshadowing a future where brands must contend with non-human customers.

AI will handle up to 80% of customer inquiries, allowing businesses to capture leads and provide support around the clock. This effectively eliminates the "9 to 5" limitation, enabling small businesses to compete with larger enterprises by never missing a customer interaction, regardless of the time.

In businesses with tight 5-8% margins, like retail, AI-driven efficiencies in areas like customer support aren't just incremental. They become extraordinarily powerful levers for profitability and scaling, fundamentally altering the cost structure of the business.