Use case / Sales
Fund the AI motions that create pipeline.
Connect seller-level AI consumption to meetings, qualified pipeline, opportunity progression, and revenue, then reinforce the workflows and spend bands associated with better outcomes.
Who it is for
CRO / Revenue
Own seller productivity, pipeline creation, and the operating choices that determine where incremental AI capacity should go.
Arbitir gives Revenue leaders a rep- and team-level view of AI capacity next to pipeline creation and conversion, so capital can follow the motions that improve selling productivity.
- “Which roles get the most from incremental AI capacity?”
- “What are my teams spending on?”
- “Where is spend misaligned with role and output?”
- “Where do returns appear to saturate?”
- “How can I evaluate spend versus revenue outcomes?”
- “Which power-user practices should be scaled across the team?”
Outcomes
What an Enterprise AE is measured on.
The outcomes your CRM already reports, with the lag each one carries and what a unit costs.
| Outcome | Horizon | Reads at | 90 days | AI cost per unit |
|---|---|---|---|---|
| Opportunities created | Proximal output | +7d | 318 | $79 per opportunity |
| Pipeline created | Proximal output | +7d | $18.2m | $0.0014 per dollar |
| Closed won | Financial outcome | +30d | $4.24m | $0.0059 per dollar |
Opportunities move within a week. Closed won matures for a month behind them.
Value model
Connect capacity to the function's operating outcomes.
Each use case runs the same Arbitir loop: observe capital, define output, measure what changes, move the allocation, and scale what works.
- 01
Spend by rep and role
Compare AI intensity by seller, segment, and team without hiding behind company-wide averages.
- 02
Pipeline unit economics
Track AI cost alongside meetings, qualified pipeline, opportunities, and closed-won revenue.
- 03
Evidence-backed expansion
Use interventions and tests to learn where incremental capacity is justified.
- 04
Playbook distribution
Turn productive behaviors into repeatable operating practice.
How Arbitir helps
Rep-level economics
Connect AI consumption to individual sellers, teams, roles, and territories, then compare it with meetings, opportunities, pipeline, and closed-won revenue.
Outcome-linked budgets
Give teams and reps AI capacity within defined budgets while capturing why incremental spend is requested and which selling outcome it is intended to improve.
High-return playbooks
Identify sellers and workflows where additional AI capacity is associated with stronger performance, then turn those patterns into recommendations that can be replicated across comparable reps.
Start allocating AI spend toward what works.
We grant access to a select number of companies each month, based on fit. Describe how AI spend is governed today and we will respond within two business days.