TokenOps Zero Integration Sprint

Synthetic data
Portfolio view & Scoping Principles

Spend, usage, ownership, and control

Use existing data first; reconcile dollars separately; map owners only where decisions change.

90-day synthetic window
The practical question
Where is AI spend already visible with the least effort?

Use existing product and billing data first. Reconcile dollars later. Avoid new accounting codes until the highest-value decisions are clear.

Design principle
Existing data → existing owners → targeted exceptions.

Resolve only the economically significant unknowns. Everything else stays in a long-tail bucket until it becomes decision-relevant.

Sprint Scope See the approach →
LANE 1 · VERY LOW FRICTION

Employee AI

Microsoft 365 Copilot / Chat
  • 80% of paid seats are active
  • Adoption varies by department
  • Inactive seats = cost recovery opportunity
View Employee AI details
LANE 2 · LOW FRICTION

Developer AI

GitHub Copilot / IDE agents
  • 81% of paid seats are active
  • Adoption concentrated in top teams
  • Inactive seats = cost recovery opportunity
View Developer AI details
LANE 3 · MODERATE FRICTION

API + Agent AI

Cloud AI spend
  • $61.5k cloud AI spend in 90 days
  • 20% of spend lacks a clear owner
  • One workload spiked 14× baseline
View API + Agent details
LANE 4 · SELECTIVE FOLLOW-UP

Shadow AI

Finance reconciliation
  • $43.6k in unmanaged AI tools
  • 7 vendors outside central procurement
  • Reconciliation layer, not primary source
View Shadow AI details

90-day spend by lane

licenses + usage + reconciled shadow

Weekly portfolio cost

total across all lanes

Prioritized findings

Sprint Scope & Strategy

TokenOps Zero-Integration Sprint Scope

Start with existing product and billing data. Add owner mapping only where it changes a capital decision.

Implementation Strategy
The practical question
Where is AI spend already visible with the least effort?

Use existing product and billing data first. Reconcile dollars later. Avoid new accounting codes until the highest-value decisions are clear.

Design principle
Existing data → existing owners → targeted exceptions.

Resolve only the economically significant unknowns. Everything else stays in a long-tail bucket until it becomes decision-relevant.

LANE 1 · VERY LOW FRICTION

Employee AI

Microsoft 365 Copilot / Copilot Chat
  • Compare licensed and active users
  • Spot underused departments
  • Quantify seat-recovery value
Jump to Employee AI dashboard
LANE 2 · LOW FRICTION

Developer AI

GitHub Copilot / IDE agents
  • Compare licensed and active users
  • Spot underused teams
  • Quantify seat-recovery value
Jump to Developer AI dashboard
LANE 3 · MODERATE FRICTION

API + Agent AI

Cloud billing + provider / gateway telemetry
  • Track cloud AI spend by workload
  • Flag unowned consumption
  • Watch for usage spikes
Jump to API + Agent dashboard
LANE 4 · SELECTIVE FOLLOW-UP

Shadow AI

SSO / CASB / expense / AP
  • Find duplicate or unknown vendors
  • Size unmanaged spend
  • Prioritize procurement follow-up
Jump to Shadow AI dashboard
Approach

How we keep the sprint light

Use what you already measure. Add mapping only where it changes a capital decision.

What we need next

A short working session with the owners of Microsoft 365, GitHub, and cloud billing. We start with what they already see — no extracts, no projects, no new accounting codes.

"Show us what you already measure. We'll design the minimum data request needed to make each decision."
Lane 1

Employee AI

Microsoft 365 Copilot seat utilization and cost.

Very low friction

Seat utilization by department

active 30d ÷ licensed
Lane 2

Developer AI

GitHub Copilot seat utilization and team activity.

Low friction

Team activity

by coding suggestions, last 30 days
Lane 3

API + Agent AI

Cloud AI consumption and ownership gaps.

Moderate friction

Daily API cost

highlighted anomaly
Attention: One workload spiked to 14× baseline while owner tags remain unresolved. Worth a budget-guardrail and ownership discussion.
Lane 4

Shadow AI

Unmanaged AI spend outside primary tools.

Selective follow-up

90-day spend by vendor

finance reconciliation layer