Multicloud FinOps Agentic Intelligence

Rogers cloud economics & AI cost governance command center

AzureAWSGCPFY26 Q3 · Updated 04:00 UTC

Scenario Planner

Model the forecast drivers

Adjust AI growth, workload placement and committed capacity adoption. Quarter-end spend, budget variance and overrun risk recalculate immediately against the approved FY26 Q4 budget.

Forecasted quarter-end spend

$30.4M

+$0.0M vs baseline

Variance to budget

+$2.9M

Approved budget $27.5M

Annualized overrun risk

$9.4M

+$0.0M

Savings from levers

$0.0M

in-quarter, placement + commitments

Forecast drivers

Assumptions applied from October onwards, ramped over the quarter

AI / model spend growth

12% MoM

Inference, fine-tuning and agent execution compounding month over month.

Workload placement shift

0% of eligible

Share of placement-eligible workloads moved to the lowest-cost provider.

Reserved capacity adoption

38% coverage

Reservations, Savings Plans and CUDs across eligible compute. Today: 38%.

Agent-recommended scenarios

Scenario vs budget vs baseline

Monthly projected spend, $M

Over budget $2.9M

Change vs baseline quarter ($M)

AI spend this quarter$7.2M
Placement savings−$0.0M
Commitment savings−$0.0M
Implied annual run rate$121.5M

At these assumptions the group closes the quarter $2.9M over budget. Holding AI growth below 6% per month is the single highest-leverage move.