Artificial Intelligence promises speed, automation, and insight. Yet in real-world software projects—especially enterprise, GovTech, ERP, and industrial systems—AI often breaks systems instead of improving them.
This usually does not happen because AI models are "bad", but because they are applied with the wrong mental model.
This article documents common anti‑patterns we see when AI is introduced into production systems, why they fail, and how experienced software developers can avoid them.
