Discovery is the phase where organizations move from abstract interest in an AI solution to concrete understanding. The focus is not on tools or pilots, but on identifying where AI solutions can realistically improve outcomes, reduce friction, or unlock new capabilities.
In this phase, teams clarify objectives, constraints, and success criteria. Poor Discovery leads to misaligned pilots, wasted spend, and skepticism later in the adoption journey.
Discovery is about deciding what not to do as much as what to pursue.
The AI Altitude Model (AAM) is a staged operating framework that helps organizations understand where they are in their AI adoption journey and what is required to safely progress from experimentation to full operational control and sustained value realization.
The end-to-end operating system that governs how organizations discover, deploy, adopt, and scale AI.
A structured model that maps AI initiatives from experimentation to sustained operational impact.
A structured method for identifying and prioritizing AI opportunities tied to real value pools.
A clear articulation of intent that aligns teams without prescribing tactics.
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