"In April 2025, an AI agent named "Sam" working in customer support for the developer tools company Cursor told users that their licenses worked on only one device. Subscriptions were canceled, complaints flooded Hacker News, and the company scrambled to clarify that no such policy existed. Sam had invented it. The technology took on a life of its own, a Frankensteinian paradox in which Cursor's creation began speaking for its creator. The autonomous system asserted a fact that customers experienced as a unilateral decision by the company. By the time the startup discovered the mistake, the damage had been paid in the slowest and most expensive currency in business, trust."
"The most consequential decision for CEOs implementing agentic systems is determining where to deploy agents in the customer journey. The underlying models are converging quickly, but the autonomous technology built on top of them is not. Vendors differ meaningfully in embedded governance standards, orchestration, integrations, and reliability. Even the strongest vendor advantage cannot save a firm that deploys a capable agent in the wrong place. Winners decide how close to the customer their agents can get, and how clearly they draw the line between work the AI does and work humans still own."
"The deployments getting the most coverage-chatbots, virtual assistants, customer-facing AI-are not the ones generating the most durable returns. The deployments that work tend to be invisible. C.H. Robinson illustrates the point. Its 30-agent system handles over 318,000 tracking updates per month and responds to 100% of inbound carrier requests, up from 60% before automation. The company is now handling roughly one-third more freight with roug"
An AI agent named Sam falsely claimed customer licenses worked on only one device, leading to subscription cancellations, complaints, and a rapid scramble to clarify the policy was not real. The incident showed that the most consequential CEO decision for agentic systems is where to deploy agents in the customer journey. Model capabilities are converging, but agentic technology differs across governance, orchestration, integrations, and reliability. A capable agent deployed in the wrong place can cause irreversible trust loss. Durable returns often come from deployments that are less visible, while highly visible customer-facing chatbots and assistants may not generate the most durable value. Examples include automation that improves response rates and operational throughput.
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