The Two Metrics That Actually Prove AI ROI | Deep Geeks ep04

If it takes a complicated logic chain to explain your AI ROI to a customer, it is probably not the ROI story that lands. https://www.weka.io/podcast/?utm_source=youtube&utm_medium=social In this clip from DeepGeeks Episode 4, an investor makes the case that most AI ROI frameworks are overbuilt. The example is Octopus Energy, the leading electricity retailer in the UK, which has spent two to three years deploying AI through its Kraken software platform to change how customer service messages get handled. Octopus never needed a new AI scorecard, because it already had two North Star metrics. Does this improve the efficiency of the team? Does this improve the happiness of customers? They have proven AI does both. That is the ROI. No attribution modeling required. The harder territory is internal productivity, particularly anything touching R&D velocity. The industry has already moved from lines of code to commits, and is now moving toward features and business value delivered. Those are genuinely difficult to measure. But when a company has a clear mission, the test stays simple: hit efficiency and customer happiness at the same time, and you know you are winning. Learn more: Listen to the full episode: https://www.weka.io/podcast/?utm_source=youtube&utm_medium=social&utm_content=full-episode WEKA NeuralMesh: https://www.weka.io/product/neuralmesh/?utm_source=youtube&utm_medium=social&utm_content=product-page Subscribe for more AI infrastructure content: https://www.youtube.com/@WekaIO?sub_confirmation=1