Your AI advisor uses AI. That means you are not buying a report — you are buying a decision engine. The question nobody asks is the most important one: who is watching it while it works, and by what standard? If the methodology is AI-powered, how do you know it is not hallucinating, drifting, or pattern-matching? Most AI-assisted methods are prompt libraries with production values. An adversarial methodology is structurally different — and must hold itself to the same standar

AI is no longer a tool inside your workflows. It is becoming an actor within them. Agents plan, decide, and act — without waiting for instructions. A tool does what you tell it. An agent does what it interprets you meant. The gap between those two things is where your next crisis lives.

Organizations are scaling AI capability faster than they are scaling understanding. 100 trillion tokens of real-world usage data reveal an uncomfortable truth: AI value doesn't come from model capability — it comes from fit. And fit is exactly what most AI strategies don't test.

99% of executives call AI a top priority. Just 2% have restructured based on proof it works. The rest are acting on belief. Three curves determine whether AI creates value — and almost nobody tracks the one that matters most.