The Jameel Jahanian Framework (JJF): A Unified Measurement Index for Institutional AI Readiness Debt Across Cognitive, Systemic, and Trust Dimensions V 1.2

Organisations worldwide are adopting artificial intelligence at unprecedented speed. Yet thedominant frameworks for evaluating AI deployment risk remain fragmented, addressingeither technical failure, cybersecurity exposure, or workforce readiness in isolation. Noneprovides a unified, measurable model for the compound damage that occurs simultaneouslyacross three dimensions when AI enters an unprepared institution.This paper introduces the Jameel Jahanian Framework (JJF), a novel unified measurementframework that quantifies the hidden cost of AI adoption across three co-occurringdimensions: cognitive debt, systemic integrity debt, and trust capital debt. The frameworkdefines three sub-indices, a weighted composite score (0–100), risk thresholds, andapplication pathways.The JJF score is defined as a weighted composite of three sub-indices: the Cognitive BurdenRatio (CBR), the Systemic Integrity Score (SIS), and the Institutional Trust Coefficient (ITC). Aformal mathematical model is proposed, threshold categories are defined, and real-worldapplication pathways for enterprise, regulatory, and policy contexts are outlined. JJF isdesigned to function as a pre-deployment governance instrument, enabling organisations toidentify AI readiness debt before it becomes irreversible institutional damage.No existing framework - commercial, academic, or regulatory — currently addresses allthree dimensions within a single measurable construct. JJF fills this gap.

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