SAAF Consumption-Based Pricing Planner

Time to Complete: 60–90 minutes (initial setup), 30 minutes monthly (ongoing)

Purpose: To help procurement and finance teams forecast, monitor, and control AI service costs under a consumption-based pricing model. Ensures alignment between budget and actual AI usage.

Why Use This?

AI costs can quickly escalate if usage isn't carefully managed. This tool provides structured guidance to estimate expected expenses accurately, proactively track actual usage, and implement controls to prevent overspending.

Step 1: Identify AI Service and Usage Metrics

• List the AI services being utilized (e.g., Rovo, AWS Bedrock, Google Vertex AI).

• Define the billing metric (e.g., tokens, API calls, compute hours).

Step 2: Estimate Monthly Usage

• Engage technical teams to provide realistic monthly usage forecasts.

• Calculate usage under various scenarios: low, average, and high.

Example Calculation:

• Service: OpenAI LP (GPT-4)

  • Average monthly queries: 10,000

  • Tokens per query: 1,500 (500 input + 1000 output)

  • Rate: $0.03 per 1,000 input tokens; $0.06 per 1,000 output tokens

  • Monthly cost calculation:

    • Input: 10,000 queries × 500 tokens/query × ($0.03/1000 tokens) = $150

    • Output: 10,000 queries × 1,000 tokens/query × ($0.06/1000 tokens) = $600

    • Total monthly cost = $750/month

Step 3: Set Budgets and Alerts

• Use vendor dashboards (Azure Cost Management, AWS Cost Explorer, Google Cloud Billing) to establish monthly spending limits.

• Configure automated alerts at 50%, 75%, and 100% of the monthly budget.

Step 4: Monitor and Track Usage

• Schedule bi-weekly reviews of usage data against the forecast.

• Identify trends or unexpected spikes and investigate promptly.

Step 5: Optimize and Control Costs

• Evaluate opportunities to reduce usage or switch to more cost-efficient models or methods.

• Implement usage limits or throttling mechanisms for non-critical AI services.

Step 6: Review and Adjust Regularly

• Monthly: Compare actual vs. forecasted usage and adjust forecasts.

• Quarterly: Revisit vendor pricing terms, explore hybrid or commitment models if usage stabilizes.

Implementation Tips:

• Assign clear ownership for cost tracking and optimization.

• Ensure technical teams understand cost implications of AI service usage.

• Maintain transparency by regularly reporting AI costs to key stakeholders.

This structured approach promotes proactive cost management, ensures predictable budgeting, and maximizes value from your AI investments.