Measure First: Meters, Dashboards, and Honest AI Energy Reporting

Both the Green AI Institute’s 2025 white paper and the Oxford TIDE energy notes hammer one theme: you cannot green what you do not meter. A Kenyan media house started with clamp meters on server racks and a simple Grafana board. They discovered nightly batch jobs were burning more than daytime live streaming. By shifting those jobs to solar-heavy hours and retiring two underused servers, they cut monthly energy by 18% with almost no capex. Copy their flow: (1) Meter or estimate AI workloads separately—CPUs, GPUs, edge boxes; (2) Tag jobs with kWh, gCO2e, and cost; (3) Publish a monthly AI energy and carbon snapshot; (4) Pair the data with interventions such as right-sized models, carbon-aware scheduling, or heat reuse. Credible reporting builds trust with finance, helps ESG teams cite real Kenyan numbers, and makes optimisation decisions obvious instead of theoretical.