Back in 2019, I wrote about the need for data hygiene in the run-up to the launch of the Mechanical Licensing Collective (MLC). My argument then was straightforward: If music publishers wanted to operate effectively in a more data-driven environment, they had to get serious about the quality, consistency and accessibility of their information. Seven years later, publishers are asking most prominently: How do we take advantage of AI?
For many music publishers, AI can be genuinely useful. But too many organizations are starting in the wrong place. They begin by asking which vendor to use, which model to test or how quickly they can deploy a new tool. Those are not the right questions. The real jumping-off point is much simpler: What exactly are we trying to fix?
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The Real Problem
For most music publishers, the real obstacle is not technology-related. Rather, it is fragmentation — the same issue they were having back in 2019. Throwing more tech at any problem rarely resolves it. In fact, when systems, workflows and responsibilities are misaligned, AI tools do not create clarity. Instead, they amplify inconsistency, highlight contradictions and make weak foundations more visible.
