AI sourcing tools promise intelligence, but many still rely on keyword matching and embeddings that surface “similar” text, not true fit. That’s why you get candidates who mention engineering instead of engineers, or “analysis” instead of analysts. These systems miss context and depth, reward keyword stuffing, and overlook top talent who don’t write for algorithms. This session breaks down why sourcing AI fails and what to look for in tools that find signal, not noise—so you get candidates you actually want.