Revenue reclassification
Revenue reclassification is the repricing of a company's revenue because AI changed how likely it is to stay, not how large it is. Buyers still pay for sticky revenue; AI changes what counts as sticky, so, as in a credit downgrade, the revenue stays the same, the label changes and the price follows the label.
Worked example
Illustrative numbers. Two companies each have $5M in annual recurring revenue.
| 2021 | 2026 | |
|---|---|---|
| Software for small businesses, switch-out takes 30 days | Sticky: about 17x revenue, $85M | Replicable: a rival imports the data in seconds; priced like services revenue at 3–4x, $15–20M |
| Services to a hard-to-reach professional group, delivered with AI at lower cost | Services: 1–2x revenue | Sticky again: outcomes improve and the customers are costly to win elsewhere; priced at a premium to services |
Neither company's revenue changed. Its class did.
What moves revenue down a class
- The product can be rebuilt by a competitor or a lab within two years.
- Switching takes minutes, because data moves automatically.
- Most of the price is passed through to the model provider, leaving a thin margin.
What moves it up
- The customers are hard to reach and tightly defined.
- The provider delivers the outcome, not the tool.
- Serving the customer produces data nobody else has.
How it differs from
- Multiple compression. Compression lowers prices across a whole market. Reclassification sorts revenue inside it: some moves down a class, some moves up.
- Churn. Churn is customers leaving. Reclassification is the buyer pricing in that they could leave, before they do.
Questions
Does this mean software is worth nothing? No. Software tied to a hard-to-reach customer group can be worth more than before; the code itself is worth less.
How do buyers check the class in diligence? They look at how long a rebuild would take, how fast customers could switch, and how much of each dollar goes to the model provider.
Origin
Set out by Viktoria Izdebska at izdebska.com (2026), building on How AI Companies Will Get Acquired.