Conceptual Study on the Depth of Thought Model (D = O \times A \times U) and Outcome Creation Capacity in the Generative AI Era

Abstract

Abstract This paper presents a conceptual approach to capturing the tectonic shift in individual outcome-creation structures driven by the widespread adoption of Generative AI. Human cognition is defined at its core as the "Depth of Thought (D)," modeled as the multiplicative product of three factors: Observation (O), Altruistic & Multi-perspective Vision (A), and Utility & Profit Understanding (U), such that D = O \times A \times U. While performance in traditional non-AI environments was a linear (first-order) model proportional to time input, under a Generative AI co-creation environment, the Depth of Thought D itself functions as an internal execution multiplier (k). This paper formalizes the mechanism that generates non-linear, explosive growth accompanied by quadratic leverage (k^2). Furthermore, it proposes a framework for applying this model to organizational talent placement (Growth-oriented, Maintenance/Operations, and Balancers) and dynamic governance in nation-scale project evaluations.