Enterprise AI has a new vanity metric: tokens consumed. Companies are bragging about millions, billions, even trillions of tokens as if massive compute usage somehow proves their AI strategy is working. It doesn’t. In this video, Domo CMO Mark Boothe breaks down why skyrocketing token consumption is often a symptom of disconnected systems, poor data architecture, weak governance, and inefficient AI workflows. Because the real challenge in enterprise AI isn’t generating more prompts. It’s creating better context. Topics covered: • Why token consumption is becoming a misleading AI KPI • The hidden cost of disconnected enterprise data • Why large language models struggle with messy business context • The difference between brute-force AI and intelligent orchestration • How governed, connected data dramatically improves AI efficiency • Why context matters more than compute in enterprise AI The companies that win in AI won’t necessarily spend the most. They’ll build the cleanest intelligence layer, the strongest governance model, and the most efficient path from data to action. That’s the future Domo is building toward. See how Domo helps you build a more efficient intelligence layer: https://bit.ly/3RCj2A3 #AI #EnterpriseAI #LLM #DataGovernance #AgenticAI #ArtificialIntelligence

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