This paper introduces the GAWM Operational Framework, a two-stage assessment model for diagnosing organizational awareness failures. Although the framework is designed for general organizational use across any capability integration challenge, it addresses with particular urgency the conditions of the current AI era, where the cost of organizational opacity has become measurable, immediate, and public. The framework bridges three established bodies of knowledge: TOGAF enterprise architecture layered model, DIKW information hierarchy moving from Data through Information and Knowledge to Wisdom, and GAWM awareness dimensions of Ground, Awareness, We/th, and Mind. The central claim is that AI value failures are not random. They are structurally predictable from the specific points at which awareness breaks down between architectural layers, and those points can be identified before deployment rather than after. The paper proposes awareness checkpoints at each TOGAF layer transition, grounded in DIKW flow logic, and derives two assessment instruments: a four-question GAWM Diagnostic suitable for any leadership team without technical prerequisites, and a structured GAWM Deep Assessment for enterprise architects, transformation leaders, and organizational advisors who need to map organizational awareness before any significant deployment, whether AI, platform, or process transformation. Falsifiable predictions are derived for each checkpoint. The framework is grounded in documented organizational patterns from Toyota, Microsoft, and the McKinsey AI research corpus, examining both where awareness flow produced value and where its absence produced failure.
BUSRA ODACI (Fri,) studied this question.