AI Budget Management Intermediate

Budget management prevents AI cost overruns by setting spending limits, configuring alerts at multiple thresholds, implementing approval workflows for expensive resources, and forecasting future costs based on usage trends. This lesson covers practical budget management for AI teams.

Budget Structure for AI

• Organization budget - Total AI spend cap for the company
• Team budgets - Per-team monthly allocation based on planned projects
• Project budgets - Per-project budget with defined GPU-hours and timeline
• Experiment budgets - Per-experiment caps to prevent runaway training jobs

Budget Alert Thresholds

Spend Forecasting

Forecast AI costs using historical patterns and planned projects:

• Trend-based - Linear regression on historical daily spend to project month-end costs
• Project-based - Estimate costs for planned training runs, experiments, and new model deployments
• Seasonal adjustment - Account for cyclical patterns (end-of-quarter model refreshes, holiday traffic spikes)

Approval Workflows

Require approval for expensive AI resource requests:

• Large GPU requests - Any request for 8+ GPUs requires team lead approval
• Long-running jobs - Training jobs estimated to exceed $1,000 need project manager sign-off
• New instance types - First-time use of expensive GPU types (H100, A100) requires FinOps review
• On-demand in production - Using on-demand instead of reserved/spot requires justification