Notes on deploying.
Or: on what change management knows about the AI race.
The capital is moving. The conversation is loud. For three years the question that absorbed the field was which model is best. It is starting to be which deployment is real, and against which existing systems. Companies that call themselves AI-native are not exempt. Companies that don't are even less so. The next two years will involve rethinking work that has not been touched in a long time.
That part of the work has a name. Practitioners have been refining it for twenty years.
The race moved
The model layer has not finished moving, but it is no longer the constraint that decides outcomes. Capability is, increasingly, a given. Useful, trusted, repeatable intelligence inside a real organization is not.
On a November evening in 2022, I was sitting next to a team that had been deep inside the pre-chat versions of these models for months, sure we were the creative people in the room. We were not. The week that followed put the ceiling on capability ten feet higher than any of us had thought to look. The constraint, it turned out, was access.
The constraint has moved again. It is now neither capability nor access. It is what happens after both are in the room.
The discipline has a name
The book Rewired, by Rodney Zemmel and his co-authors at McKinsey, names the building blocks of digital and AI transformation in a way that is useful to anyone who has worked inside one. There are six: strategy and roadmap; talent; operating model; technology; data; adoption and change management. None of them are new. None of them are AI problems.
The reason Zemmel and his co-authors take the time to name them is that practitioners keep skipping the ones they find hardest. Anyone who has done a platform replacement in financial services has lived through some version of each. The terminology is McKinsey's. The work is older.
The two everyone names
Of the six, talent and technology are the easiest to put into a slide deck, a board update, a CEO town hall. A certification cohort is countable. Enterprise model access can be committed to in writing. A center of excellence is photogenic.
These are real, and useful. They are also the two of the six that the conversation has been built to carry. The market right now names them well. It mostly stops there.
That is not a complaint. It is an observation about which parts of a transformation public attention can carry, and which parts it cannot.
The four it doesn't
Strategy and roadmap. Operating model. Data. Adoption and change management.
There was a State Street accounting platform replacement I worked on at a global asset manager, twelve front-office business groups end to end, several hundred reports across roughly seven hundred users that we eventually got down to several dozen. The piece of work that decided whether the replacement was honest was a piece nobody had asked for: a capabilities assessment that took the prework question seriously. Years earlier, a Cambrian capabilities assessment for an insurance asset management business surfaced the same lesson. The assessment phase is the underpaid phase. It is also the phase that decides the rest.
The conversation right now describes deployment. It mostly does not describe the discipline that converts capital and talent into outcomes. That conversion is not allocated by a deal or a vendor contract. It is done by people, on the inside, over a longer horizon than a news cycle.
Where the stakes are
There was a multi-year program at an asset manager where, by the second year, the traders gave me a seat on the trading floor. The seat was earned by discovery work, not by the project plan. There was a stress-testing program where a data-corruption issue resolved only because someone, six months from retirement, remembered why a particular shortcut had been inserted into the data flow years earlier. It was not in documentation. It was in his head.
Both stories are about deployment. Neither is about capability.
The new tools don't change the disciplines. They raise the stakes on them.
This is the part of the work that does not surface in a market briefing or a quarterly letter. It is also the part of the work that decides whether the headline numbers ever happen.
On purpose
The capital is real. The capability is real. The excitement is real. The discipline that decides outcomes has been understood for a long time, by practitioners who have lived through enough digital and AI transformations to know what gets skipped and at what cost. The opportunity now is to do that work on purpose, at the scale the moment makes possible.
That is, in fact, the good news.
// DG