Skip to content

1. Template: Business Case & The Cost Overview

1. Purpose

This template helps to quantify the business value and map the total operating costs of an AI solution.

Download this template

Download as Markdown — Open in your editor or AI assistant and fill in the fields.

Value Hypothesis

What is the expected gain?

  • Efficiency gain: [E.g. Number of hours saved per month.]
  • Quality improvement: [E.g. Reduction in error rate.]
  • Revenue growth: [E.g. Higher conversion through personalisation.]

The Cost Overview (TCO)

What are the total costs for development and management?

  • Investment (Capex):
  • Team hours (Project Management, Data Science, Engineering).
  • Initial data acquisition or tooling.
  • Usage Costs (Opex):
  • API / Token costs per month.
  • Compute / Hosting (Cloud).
  • Maintenance & Monitoring by team.

ROI & Payback Period

  • Net return: [Value - Costs].
  • Payback period: [Months to break-even].

Environmental Footprint

Mandatory field for all systems with continuous inference or scalable rollout.

Aspect Estimate / Notes
Inference intensity [Low / Medium / High — calls/day + model type]
CO₂ estimate (inference) [kg CO₂eq/month — use provider dashboard or tool]
Training costs (if applicable) [Not applicable / kg CO₂eq one-time]
Comparison with baseline [Current process vs. AI system — net impact]
Optimisation measures [E.g. model quantisation, batch inference, caching]

Green AI Guideline

Refer to the Green AI standard for calculation tools and thresholds. For systems with >1,000 calls/day, a detailed calculation is required.