The Evergreen Ratio
A financial diagnostic metric representing the ratio of fixed-cost software revenue (traditional SaaS features) to variable-cost AI revenue within a product portfolio. A high Evergreen Ratio indicates a stable, high-margin business with strong structural safety. A declining Evergreen Ratio signals that a company is becoming dangerously dependent on high-COGS AI features, exposing it to AI margin squeeze and severe valuation compression.
“Trading zero-marginal-cost software for high-variable-cost AI is a dangerous economic bargain.”
As traditional SaaS companies rapidly bolt on AI features, they are unknowingly altering their fundamental economic structure. They are trading high-margin, predictable revenue for low-margin, variable-cost revenue. If the Evergreen Ratio drops too low, the company ceases to be a highly valued software company and begins to look economically like a low-margin services or manufacturing business. Tracking this ratio is essential for maintaining enterprise value during an AI transition.
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The Evergreen Ratio
A financial diagnostic metric representing the ratio of fixed-cost software revenue (traditional SaaS features) to variable-cost AI revenue within a product portfolio. A high Evergreen Ratio indicates a stable, high-margin business with strong structural safety. A declining Evergreen Ratio signals that a company is becoming dangerously dependent on high-COGS AI features, exposing it to AI margin squeeze and severe valuation compression.
Direct Relationships (3)
Transitive Neighbors (Connected via Hop 1)
Extended Causal Ripple Effects
Richard Ewing’s Research Thesis
Companies must actively manage their Evergreen Ratio to prevent their SaaS valuation multiples from collapsing.
Why This Specification Exists
SaaS companies are bolting on AI features and destroying their own gross margins.
Treating all ARR as equal value.
No board-level metric identifying the specific risk of high-variable-cost AI revenue dilution.
A ratio tracking the balance between zero-marginal-cost software and high-variable-cost AI.
What Changes If You Believe This?
Teams must balance AI integrations with high-margin deterministic features.
Segments revenue streams to monitor the structural health of the business.
Designs AI features specifically to funnel users into evergreen retention loops.
N/A
Recommended Action by Role
Balance zero-marginal-cost SaaS revenue against high-variable AI features to protect software valuation multiples.
Resist AI hype that dilutes recurring gross margins into low-margin professional services.
Segment AI API compute costs from core software subscription revenue in quarterly board reporting.
Design AI capabilities specifically to funnel users into sticky, evergreen retention loops.
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Frequently Asked Questions
Q:Why is it called "Evergreen"?
Because traditional SaaS revenue is "evergreen" - once the code is written, it generates revenue repeatedly with near-zero marginal cost.
Q:Should a company aim for a 100% Evergreen Ratio?
No, that would mean ignoring AI entirely, which risks obsolescence. The goal is balance: using AI to drive adoption while relying on evergreen features to drive margin.
Canonical Specification Origin
Companies must actively manage their Evergreen Ratio to prevent their SaaS valuation multiples from collapsing.
Corpus Interconnections
Richard Ewing artifacts developed around this canonical framework, including publications, execution tools, and diagnostic models.
External Adoption & Peer Citations
Documented instances where independent researchers, engineering teams, and publications have cited, implemented, or referenced this concept outside Richard Ewing’s ecosystem.
External Evidence: No independently verified references recorded yet.
This concept is part of Richard Ewing’s original baseline canon. External citations and implementations are added only upon rigorous empirical verification.
Inspectable Evidence Ledger
Classified evidence items supporting, extending, or refining this canonical research specification.
Recommended Citation
Ewing, R. (2026). "The Evergreen Ratio." Richard Ewing Research Canon. Available at: https://www.richardewing.io/concepts/evergreen-ratio
@article{ewing_evergreen_ratio,
author = {Ewing, Richard},
title = {The Evergreen Ratio},
journal = {Richard Ewing Research Canon},
year = {2026},
url = {https://www.richardewing.io/concepts/evergreen-ratio}
}