Post by Paul Brzozowski

J.P. Morgan Chase just deployed agentic AI to 250,000 employees. Here's the problem most enterprises are missing. J.P. Morgan can answer one question that 95% of companies can't: "Which AI agents are delivering ROI, and which are wasting budget?" They built LLM Suite as a governed, measurable platform from day one. Every agent, every workflow, every use case is connected to their intelligence layer. Most enterprises? They're deploying agentic AI in the dark: - Shadow workflows proliferating with zero visibility - No way to measure cost per task or success rates - C-suite demanding ROI proof after the fact Pilots everywhere, scale nowhere. The gap isn't about AI spend. It's about intelligence. J.P. Morgan projects $2B in annual value because they solved the measurement problem first. They know what's working. You're still guessing. The shift to agentic AI makes this 10x harder. Autonomous agents operate across systems, make decisions, trigger actions without human intervention. Ask yourself: - How many agentic workflows are running in your organization right now? - Can you prove which ones justify continued investment? J.P. Morgan can. Most enterprises can't. The winners in this phase will have three things: 1. Visibility across the entire AI stack (Agents, GenAI, SaaS AI) 2. Measurement tied to business outcomes (cost, productivity, ROI) 3. Governance infrastructure that enables scale You wouldn't run a company without a CRM or ERP. Why are you scaling AI without a system of record to measure it? Read the full breakdown in the article (link in comments). Your competitors are deploying agentic AI right now. Some are measuring it. Most aren't. Which side are you on? #AIGovernance #EnterpriseAI #AgenticAI #AIIntelligence #AITransformation #Olakai #AIFund #JPMorganChase #GenAI #AIStrategy #AImeasurement #OlakaiIntelligencePlatform