Rule of 40 vs. Rule of 60: Which Benchmark Fits Your Company?

For roughly a decade, the Rule of 40 has served as board-level shorthand for SaaS performance. Add revenue growth rate to profit margin, and a combined score of 40 or higher signals a healthy balance between investing for growth and generating returns.

AI has added two new arguments to that conversation. Some software investors, including Vista Equity Partners, describe a combined score of 60 as an emerging aspiration for companies that adopt AI successfully. On the other end of the scale, Bain & Company makes a case for tolerating scores closer to 30 while companies reinvest to compete with AI-native players.

Each argument fits a different kind of company, and whether a company should be measured by the Rule of 30, 40, or 60 is often subjective. A scaled business with strong margins and a seed-stage AI native burning cash to establish market share face different trade-offs, and both may look different again in two years.

Balancing growth and profit now involves variables the original Rule of 40 never accounted for, from inference costs to usage-based revenue. Today, reading the score well means understanding which of those variables are driving it.

How the Rule of 40 Is Calculated and Which Margin to Use

Rule of 40 Score = Revenue Growth Rate (%) + Profit Margin (%)

A company growing 30% with a 15% margin scores 45. A company growing 60% with a −20% margin scores 40. Scores are broadly comparable from one company to another, provided the following is true:

• Reporting Period: Growth and margin should cover the same trailing twelve months or fiscal year.
• Type of Revenue Measured: revenue and ARR can diverge, particularly for companies with usage-based pricing or large multi-year contracts. State which one the calculation uses.
• Profit Margin KPI: EBITDA margin measures operating profitability before interest, depreciation, amortization, and income taxes, and it is the measure private equity investors most often use when discussing Rule of 40 and Rule of 60 targets. Free cash flow margin, commonly operating cash flow less capital expenditures as a percentage of revenue, can rise when customers shift to annual upfront billing, even when underlying profitability is unchanged. It’s more commonly used for public companies. For board reporting for private businesses, EBITDA margin gives a steadier read on operating performance.

Each of these choices can shift the score, which makes a Rule of 40 result only as meaningful as the definitions behind it. A documented calculation, applied the same way every period, is what makes the number comparable over time and credible in a board or investor conversation.

Where the Rule of 60 Argument Comes From

Vista Equity Partners describes the Rule of 60 as an emerging aspiration for AI-enabled software companies, arguing that businesses using AI effectively may be able to raise growth and profitability at the same time. Vista also notes that relatively few companies achieve it today.

Another argument for adopting the Rule of 60 centers on acquisition economics. In a Rule of 60 analysis, software operator and investor Dave Kellogg models a private equity deal in which a company maintains 20% growth while raising its EBITDA margin to 40%. Under his specific acquisition, financing, and exit assumptions, that improvement moves the illustrative equity investment multiple from roughly 1.1x to roughly 3.1x. The example shows why some investors want more than 40 when they buy at high multiples. Results for any individual company depend on its own deal terms.

Some software investors are discussing targets above 40, particularly where AI productivity gains or acquisition economics support a higher growth-and-margin requirement. Whether 60 applies to a given scaled SaaS company depends on those economics and on the expectations its investors set.

Why AI Can Push Scores Down Before It Pushes Them Up

The same technology that supports a higher ceiling also raises costs in the near term. Bain & Company argues that rising AI costs are squeezing software margins, and that leadership teams may need to accept a Rule of 30 for a period while they reinvest to compete with AI-native players.

The 2026 data shows where that pressure sits. ICONIQ's 2026 State of AI report puts average gross margin on AI products at 45% in 2025, with projections of 53% for 2026 and 59% for 2027. At the company level, Benchmarkit's 2026 SaaS and AI Performance Benchmarks found median software gross margin holding at 80%, with little evidence to show that AI costs had compressed margins at the median.

Read together, those figures describe a concentrated cost. A company whose AI features are a small share of revenue may see little change in its blended margin. A company whose product experiences are dependent on AI inference will feel the cost on every customer, and its Rule of 40 score will reflect that until pricing and delivery costs catch up.

That makes the Rule of 30 argument a question of revenue mix. A useful margin figure for a board right now is gross margin on AI revenue, reported separately from the core product. A company entering a period of lower combined scores should be able to show:

• AI gross margin improving quarter over quarter
• A pricing model that passes some compute cost through to customers
• A target date for the combined score to recover

Those three signals separate a planned reinvestment from a margin problem that is getting worse. A board that sees all three can treat a lower score as part of the plan.

Interpreting the Score at Different Stages

The three hypothetical profiles below show how the same formula leads to different conclusions depending on stage and capital source.

The table points to one practical rule: compare your score against companies at a similar stage, revenue size, and margin structure, using the same margin definition. Stage-specific SaaS benchmarks give a more reliable comparison than headline figures from outlier companies.

Retention and ARR Quality Decide Whether the Score Holds

A combined score measures a single year, and retention helps show how durable that growth may be. At 70% gross revenue retention, expansion and new sales must first offset the loss of 30% of the opening recurring revenue base before producing net growth. At 95% gross revenue retention, only 5% of the opening recurring revenue base needs to be replaced before expansion and new sales contribute to net growth.

The distinction between gross retention and net retention matters here, since strong expansion revenue can mask high churn in the net figure.

Younger AI-native companies may have too little history to show multi-year cohort behavior, which makes these questions especially useful before treating growth as a reliable benchmark input:

1. How much of current ARR comes from multi-year contracts, and how much from month-to-month or usage-based plans?
2. How much revenue comes from pilots or trial conversions that have yet to renew?
3. Are gross retention rates holding steady across recent customer cohorts?

These questions sit at the core of any assessment of ARR quality.