Executive Summary

Generative systems are exceptionally good at producing more of whatever they are given. An organization without a governing definition of itself now scales its inconsistency at machine speed and reads the output as productivity.

My Perspective

The first year of generative marketing was spent asking what the tools could produce. The second is being spent discovering what they produced. In most organizations the answer is a large volume of material that is individually acceptable and collectively incoherent.

This is not a model problem. A model returns what its inputs imply. When the inputs are eleven slightly different descriptions of the same company, gathered from a website, a deck, a brief and four people’s memory, the output is eleven slightly different companies, produced faster than anyone can read them.

Governance is not a brake on AI. It is the precondition for using it seriously.

Human judgment is not removed from these systems by decision. It is removed by omission, at the point where nobody was made accountable for what the machine was told. The fix is unglamorous and it is not technical: one governing document, owned by a person, that every generated artifact inherits.

Governance in marketing has been treated as a legal function. It is closer to an editorial one. Somebody has to be responsible for what is true.

Key Takeaways

• Models scale whatever consistency an organization already has, including none.
• Judgment leaves the system by omission rather than by decision.
• The governing document is an input problem, so it has to be solved before the tooling question.
• Accountability for what is true belongs to a named person, not to a platform.