Still Growing

AI EBITDA lever sizer

Most AI readiness tools give you a maturity score. A buyer will ask a different question: how much of this shows up in earnings by the time we sell? Size AI by function, discount it for readiness, and see what is bankable at exit versus what is still a story.

The company
By function

Cost as a share of revenue, and how ready the data and processes are today.

Sales and marketing
Customer service
Finance and G&A
Operations and supply chain
Technology and R&D
What do Low, Medium and High mean?
Low
Data scattered, processes vary by site or person. Assumes about 35% of the potential is captured, reaching full run-rate in 30 months.
Medium
Core data in one system, processes mostly documented. Assumes about 65% of the potential is captured, reaching full run-rate in 18 months.
High
Clean data, standard processes, an owner ready to lead. Assumes about 90% of the potential is captured, reaching full run-rate in 12 months.
Adjust improvement assumptions

Defaults are starting assumptions for discussion, not industry benchmarks. Replace them with your own numbers. Ranges are the share of each function's cost that AI could take out at full adoption.

Sales and marketing
Customer service
Finance and G&A
Operations and supply chain
Technology and R&D
Bankable at exit –
Enterprise value at exit–
Still a story at exit–EBITDA a buyer may or may not credit
Lost to readiness–Recoverable with data and process work

By function

The clock

Annual run-rate EBITDA from AI, month by month. A buyer underwrites the trailing twelve months before close (shaded).

Add to value bridge Talk it through

Defaults are starting assumptions for discussion, not industry benchmarks. Replace them with your own numbers. Value shown is EBITDA times exit multiple, before implementation costs.

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