Full Answer

Asking whether AI can build a pipeline conflates two very different jobs. The first is generating working code to send events to a platform, and modern AI does this well, often in minutes. If building were the whole task, the answer would be a clean yes.

But a pipeline is not a script you run once; it is infrastructure that has to keep working while the ground shifts beneath it. Advertising and analytics platforms revise their conversion APIs regularly and retire old endpoints, so code that was correct last quarter starts silently failing. Real traffic brings rate limits that need retry and backoff logic, events that fail and need monitoring and alerting, and schema changes in your warehouse that ripple downstream. Security patches require human judgement about what to apply and when. None of this is captured by the moment of code generation.

Gartner's finding that fewer than half of AI projects reach production points at exactly this gap between building and operating. The realistic role for AI is as an accelerator inside a maintained system, not a replacement for maintaining one. That is also why many businesses prefer a maintained, packaged solution over AI-generated DIY: not because the AI cannot write the code, but because someone still has to own the code every day after.