Can you actually prove what your AI product is doing for customers — or are you still pointing at token counts and hoping the board nods along?

In episode #368, Ben Murray breaks down the four layers of AI measurement that every SaaS company needs to communicate internally and externally. Token usage is table stakes. The real question is whether you can move up the stack from consumption to work performed to verified outcomes to quantifiable P&L impact. Get this wrong, and your AI story falls apart in front of investors, customers, and your own finance team. Get it right, and you finally have ROI math a CFO will actually approve.

Why AI inference belongs in COGS / DevOps — and what that means for the gross margin story behind your AI features and product lines
How Salesforce's "agentic work units" framing on its latest earnings call signals where AI reporting is heading for the rest of SaaS
Where true outcome-based pricing actually lives on the pricing page (HubSpot, Zendesk, and others) — and where Agentforce was really still usage-based in disguise
How Layer 4 business impact replaces fuzzy ROI calculators with objective math
What to show your board and investors at each layer so your AI value story holds up under scrutiny

Tune in before your next board meeting — your AI story needs more than token counts.

Resources Mentioned

Ben's blog post on AI measurement and AI work units: https://www.thesaascfo.com/the-four-layers-of-ai-measurement-a-cfos-framework/
Ben's academy: https://www.thesaasacademy.com/

Why Token Usage Tells You Almost Nothing About Your AI Product's Real Value

SaaS Metrics School

Why Token Usage Tells You Almost Nothing About Your AI Product's Real Value