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This research aims to present AICOS, a framework that enhances decision-making processes in institutions by emphasizing governance and reproducibility.

July 7, 2026Open Access

AICOS: A Governance-First Architecture for Replayable Institutional Decision Intelligence Systems

Key Points

This research aims to present AICOS, a framework that enhances decision-making processes in institutions by emphasizing governance and reproducibility.
Developed AICOS as a governance-first architecture for institutional decision processes.
Modeled decisions as structured lifecycle-bound computational objects integrating various components.
Provided a repository containing the full research paper and supplementary materials.
AICOS enables deterministic replay and traceability of decisions throughout their lifecycle.
Improved governance embedding and structural integrity of decision processes in regulated settings.

Abstract

This work introduces AICOS (Artificial Intelligence Controlled Organizational System), a governance-first architecture for replayable institutional decision intelligence systems. AICOS models institutional decisions as structured lifecycle-bound computational objects integrating evidence, policy constraints, intelligence processing, execution context, and outcome feedback. The framework enables deterministic replay, traceability, and auditability of decisions across their full lifecycle. Unlike conventional AI systems focused on predictive performance, AICOS emphasizes structural integrity, governance embedding, and reproducibility of decision processes in regulated institutional environments. This repository contains the final research paper, LaTeX source files, and supplementary materials associated with the AICOS architecture.

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