Once you build a chatbot for a bad process, something interesting happens. The chatbot develops a constituency. It has a project team, a budget line, a vendor relationship, and a shiny success story in someone’s performance review. And that constituency has a strong incentive to keep the chatbot alive - even when the smarter move is to simplify the process so the chatbot isn’t needed.
This is the AI Investment Trap.
This anti-pattern isn’t unique to AI. Organizations have invested in CRM systems, ERP platforms, and other tools that ended up protecting broken processes.
What’s different with AI is that the visible win comes faster, the political cost of admitting failure is higher, and the technology starts optimizing the existing process. That makes redesign harder later. The AI investment trap is a faster, more entrenched version of a problem we’ve seen before.
The trap plays out in three stages.