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The articles here are written for leaders who are trying to make AI investment reach the income statement, and who suspect the obstacle is not the technology.

That suspicion is correct. The research is unambiguous and the mechanisms are now well-documented: governance that cannot keep pace with model capability, operating models built for a workforce that no longer exists, cost structures that treat token spend as a procurement problem rather than an engineering one, adoption that stalls not because people resist the tool but because their roles and routines were never redesigned around it. Each of these is a solvable problem. None of them is solved by a better model.

This publication is the written dimension of Dromologue’s practice. The reader assumed is someone accountable for, or impacted byn an AI programme in an organisation. Someone who has sat in the room where the pilot was declared a success and the production deployment was quietly shelved or the value somehow lost. The writing does not explain what AI is; it addresses what AI requires of the organisation around it, and why most organisations are not yet built to deliver on that requirement.

Subscribe if you want the argument in full, updated as the evidence moves.

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Everyone has AI now. But few have the operating model to fully exploit it. We write about that gap.

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