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

Organisations worldwide are adopting artificial intelligence at unprecedented speed. Yet the dominant frameworks for evaluating AI deployment risk remain fragmented, addressing either technical failure, cybersecurity exposure, or workforce readiness in isolation. None provides a unified, measurable model for the compound damage that occurs simultaneously across three dimensions when AI enters an unprepared institution. This paper introduces the Jameel Jahanian Framework (JJF), a novel unified measurement framework that quantifies the hidden cost of AI adoption across three co-occurring dimensions: cognitive debt, systemic integrity debt, and trust capital debt. The framework defines three sub-indices, a weighted composite score (0–100), risk thresholds, and application pathways. JJF contributes a composite measurement approach that integrates these three dimensions into a single index, offering a practical tool for pre-deployment assessment and ongoing governance monitoring. The JJF score is defined as a weighted composite of three sub-indices: the Cognitive Burden Ratio (CBR), the Systemic Integrity Score (SIS), and the Institutional Trust Coefficient (ITC). A formal mathematical model is proposed, threshold categories are defined, and real-world application pathways for enterprise, regulatory, and policy contexts are outlined. This framework is designed to function as a pre-deployment governance instrument, enabling organisations to identify AI readiness debt before it becomes irreversible institutional damage. No existing framework - commercial, academic, or regulatory - currently addresses all three dimensions within a single measurable construct. JJF fills this gap.

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