In episode #331, Ben breaks down the true financial and economic differences between a SaaS company and an AI company. Inspired by a tweet claiming that “SaaS metrics are broken” and that AI companies generate more absolute profit per customer, Ben puts the theory to the test using real financial modeling.

This episode walks through detailed revenue, gross margin, EBITDA, pricing power, TAM dynamics, and unit economics scenarios to determine whether AI companies actually outperform SaaS businesses.

What This Episode Covers

• Why investors are questioning traditional SaaS metrics when evaluating AI companies
• The importance of recurring revenue fundamentals, whether the company is SaaS or AI
• A side-by-side comparison of a $1M SaaS company versus a $1M AI company
• Gross margin profiles: 80 percent SaaS vs. 55 percent AI
• How EBITDA changes when OpEx is held constant
• The revenue scale required for an AI company to match SaaS gross profit
• The revenue scale required for an AI company to match SaaS EBITDA
• Why AI companies need a TAM that is 6x larger
• How pricing power tied to labor displacement can shift AI unit economics
• Modeling ARPA increases to see when AI gross profit matches SaaS
• Why the underlying P&L structure does not change, but the inputs do
• How founders should think about forecasting and financial strategy when building AI-native products

Why This Matters

• Founders embedding AI into SaaS products
• AI-native startups modeling their financial future
• CFOs and FP&A leaders forecasting revenue, cash, and margins
• Investors evaluating early-stage AI companies
• Operators building long-term company valuation strategies

Ben emphasizes that the P&L, revenue streams, cost structure, and core KPI’s still apply. What changes are the inputs—gross margin profile, pricing power, TAM, ACV, and scalability assumptions.

Resources Mentioned

• Full blog post with financial modeling examples: https://www.thesaascfo.com/the-real-economics-of-saas-versus-ai-companies
• SaaS metrics course: https://www.thesaasacademy.com/the-saas-metrics-foundation

In episode #330, Ben explains one of the most common and costly SaaS finance mistakes: failing to allocate CAC between new and existing customers. This oversight leads to misleading KPI’s, inaccurate CAC payback, flawed LTV to CAC ratios, and unreliable unit economics. Ben walks through exactly how to allocate CAC the right way, how to segment sales and marketing expenses, and why this matters for accurate revenue efficiency metrics and due diligence.

• Why fully burdened sales and marketing expenses are required for accurate CAC

• The danger of pushing all sales and marketing expenses into CAC without allocation

• How to allocate CAC between new customer acquisition and expansion

• How to segment sales teams (hunters vs. farmers) and avoid co-mingled headcount

• Allocating marketing spend based on acquisition channels

• Typical allocation benchmarks for sales (60-80% to new) and marketing (80-90% to new)

• Why accurate CAC is essential for CAC payback, LTV to CAC, and cost of ARR

• How the Cost of ARR provides a blended benchmark without requiring allocation

• Using allocation methods for businesses with multiple product lines or motions

• How to correctly calculate CAC using fully burdened sales and marketing expenses

• How to evaluate marketing economics and sales efficiency with proper allocation

• Why unallocated CAC leads to distorted financial strategy and misleading KPI’s

• How CAC allocation flows into CAC payback period, LTV to CAC, and ARR efficiency

• How to build a repeatable, defensible go-to-market metrics framework that withstands due diligence

• SaaS founders scaling beyond early customer acquisition

• CFOs, FP&A leaders, and finance teams who own KPI modeling

• Operators who need accurate CAC, CAC payback, and LTV calculations

• Investors or advisors assessing revenue efficiency and go-to-market economics

• SaaS Metrics Foundation course covering CAC, LTV, ARR, and unit economics: https://www.thesaasacademy.com/the-saas-metrics-foundation

• Coaching resources on building an accurate, SaaS-specific chart of accounts: https://www.thesaasacademy.com/saas-cfo-coaching

In episode #329, Ben Murray, The SaaS CFO, breaks down the growing debate around SaaS economics versus AI economics. A recent post claimed that “SaaS metrics are broken” and that traditional KPIs no longer apply to AI companies.

Ben challenges this idea and walks through why recurring revenue metrics still matter, how revenue models differ across SaaS and AI, and what CFOs need to understand about gross margin, unit economics, and total addressable market.

• Why claims that SaaS metrics are “broken” are inaccurate

• The difference between SaaS economics and AI economics

• Why recurring revenue metrics still apply to AI companies

• How subscription versus usage revenue impacts KPI calculation

• Gross margin expectations for SaaS vs. AI companies

• Whether AI companies truly generate more profit per customer

• The role of absolute profit versus per-customer economics

• How AI may expand TAM by targeting labor budgets, not just software budgets

• How Agentic AI affects financial modeling and cost structures

• Using ROSE (Return on Software Employees) to evaluate AI-driven ROI

• Why SaaS metrics still matter for both SaaS and AI companies

• How CFOs should evaluate margins, ARR, and revenue quality in AI models

• The difference between rate-based economics (ARPA, ACV) and volume-based economics (absolute profit)

• How to think about financial strategy when transitioning from a pure SaaS model to an AI-embedded product model

• How to assess realistic AI unit economics instead of relying on hype

• SaaS CFOs and finance leaders evaluating AI investments

• Founders embedding AI into their product and adjusting their financial models

• Operators who want a grounded understanding of real AI economics

• Investors assessing how AI shifts revenue models and margins

• Ben’s upcoming deep-dive blog post on SaaS vs. AI economics: TheSaaSCFO.com

• SaaS Metrics Foundation course for mastering KPI’s, ARR, MRR, and unit economics: https://www.thesaasacademy.com/the-saas-metrics-foundation

• ROSE metric framework for analyzing AI-driven productivity and financial systems: https://www.thesaascfo.com/saas-rose-metric/