The field guide to modern revenue enablement — what “good” looks like at each stage of growth, and how to build the function that actually moves the number.
<30%of a seller's week actually goes to selling. That number hasn't moved in years — through every wave of new tooling.Salesforce · State of Sales (2023) ↗
MIT's finding is the one that matters: the 5% that succeed with AI don't have better models. They put strategy and execution first — real workflows, with memory, context, and ownership — and let AI do the parts it's actually good at. The other 95% bolted a tool onto an undefined process and called it transformation. The gap isn't ambition, and it isn't AI. It's the operating discipline underneath.
02 · The principles of AI-era enablement
Four principles, before you build anything.
These separate the teams that compound from the teams that automate their own mess.
01Define the process firstAutomation executes your operating model — it doesn't invent one. Without a clearly defined process, there's nothing to automate, and the tool interprets the shape of the work instead of running it.Define the work · Then automate it
02Optimize what you already ownMost of the capability is already sitting inside the platforms you pay for. The unlock isn't procurement — it's activation.No net-new vendors · Activate the stack
03Prove the use case before you scale itOne workflow, proven end to end, beats ten pilots that nobody can measure. Scaling before you can prove it is how you industrialize a mess — permanently, and at speed.One workflow · Measured · Then scale
04Build for enterprise realitySecurity, privacy, governance, and control decide what actually ships. Most of what gets celebrated online never survives a procurement review. Build for what clears the bar.Security · Privacy · Control · Governance
03 · The Revenue Enablement Maturity Model
The Revenue Enablement Maturity Model: most enablement never gets past level two.
The difference between a training team and the operating system of the revenue org is maturity — strategy first, then execution, with AI as an input, not the point. Here's the curve, and where you are on it.
01Ad hoc
Random acts of enablement. Reactive, no charter, measured by activity.
02Foundational
Content and onboarding exist. Ramp is repeatable — if not yet measured.
03Aligned
Enablement maps to the revenue process: the funnel, the motion, the number.
04Strategic
Run on outcomes. Prioritized by impact; AI starts absorbing the busywork.
05Compounding
Strategy and execution lock into a loop. AI is embedded where it earns its place, and the function improves itself.