Practice 02
AI in the Deal
The thesis leans on AI, and nobody in the room can tell you whether the position holds for twelve months.
Judgement, not a checklist
The work
Nobody can confidently price AI in a deal, because it is a judgement rather than a measurement. We give you ours, with a number on it.
We assess AI in a deal like a Rubik's Cube: Defensibility, Disruption and Duplication. Can competitors copy it, can AI-first entrants outperform it, or can customers simply build it themselves? Three faces move at once and turning one turns the others, so a target that looks strong at signing can lose its place a month after close. This practice exists because that call takes judgement, and someone has to put their name to it.
The three D's
AI is a Rubik's Cube, not a checklist.
Assessed face by face, AI always looks fine. The risk lives in the turns. Defensibility asks whether the capability inside the platform is genuinely differentiated and hard to replicate. Disruption asks whether an AI-first entrant could deliver the same outcome faster, better or more cheaply. Duplication asks whether customers could build it themselves, and its commercial consequence is disintermediation: the vendor removed from the value chain. We hold the three faces together and give you a view, not a matrix.
- Defensibility: can a competitor copy the advantage, and what would it cost them now the tooling is cheap
- Disruption: could an AI-first entrant change the market the target sells into
- Duplication: could the customer recreate the product or capability without the vendor
- Real or demo: provenance, IP ownership of generated code, data lineage and licence exposure
AI across MERGE
Where AI shows up in each stage.
AI is not a one-off report and it is not a scope line. It runs through every step of MERGE, and the same team carries the view from first look to exit.
- Judgement over logic. A matrix cannot tell you whether a position holds.
- Every AI finding carries a cost, a timing and an owner.
- Lens: Merger OS™ carries the evidence, so answers are cited back to the target's own material.
01
Assess
Is the AI real or a demo, and what does the value-creation plan assume about it.
02
Diligence
Provenance, IP ownership, data lineage, licence exposure, model risk, replicability and run cost.
03
Integrate
Guardrails, governance and the 100-day plan that keeps the estate legible after close.
04
Optimise
AI enablement through the hold, and an exit narrative a buyer's diligence can survive.