AICOS — The Operating System for Decisions introduces a governance-first architecture for deterministic decision intelligence in high-impact digital systems. While modern artificial intelligence infrastructures have significantly advanced in areas such as computation, cloud infrastructure, machine learning models, and data intelligence platforms, a critical architectural gap remains in the governance and structure of decision-making processes. Most existing AI systems focus on generating predictions or recommendations. However, these systems rarely provide a structured framework that governs how decisions are derived, validated, authorized, and audited. This limitation becomes particularly problematic in environments where decisions involve high financial, operational, or societal impact, including energy infrastructure, financial systems, public policy, and critical national infrastructure. This work proposes AICOS as a new architectural layer within modern digital infrastructure: the Decision Layer. The AICOS architecture integrates evidence-based reasoning, probabilistic risk evaluation, governance enforcement, authority mapping, and deterministic decision replay into a unified system designed for high-impact decision environments. The architecture introduces several key components, including an Evidence Engine for validating information sources, a Risk Engine for quantifying probabilistic and irreversible risk, a Governance Engine for enforcing institutional rules and regulatory constraints, and an Authority Engine responsible for maintaining role-based decision legitimacy and human-final authority. In addition, the Decision Replay Engine enables deterministic reconstruction of decision pathways, ensuring transparency, auditability, and regulatory compliance. By defining a structured decision governance infrastructure, AICOS establishes a new technological category referred to as Decision Intelligence Infrastructure. Within the broader artificial intelligence stack, AICOS occupies a previously undefined layer positioned above data intelligence systems and AI model architectures. The framework is particularly relevant in sectors where decisions carry long-term consequences and require robust governance structures, including energy investment planning, financial risk management, national security systems, and public sector decision-making. This work positions AICOS as a foundational architecture for the emerging Decision Layer in AI-driven systems and proposes a governance-first approach to ensure that AI-assisted decisions remain explainable, auditable, and bound to accountable human authority.

This publication presents the foundational architecture of AICOS — The Operating System for Decisions, a governance-first decision intelligence framework designed to support deterministic, auditable, and accountable decision-making in high-impact digital environments. The work introduces the concept of a Decision Layer within the modern artificial intelligence technology stack. While existing digital infrastructures provide layers for computation, cloud infrastructure, machine learning models, and data intelligence, the governance of critical decisions remains largely undefined. AICOS addresses this gap by proposing a structured infrastructure dedicated specifically to decision authority, risk governance, and deterministic decision lineage. The AICOS architecture integrates multiple functional components, including evidence validation mechanisms, probabilistic risk assessment, governance rule enforcement, authority hierarchy mapping, and replayable decision history. This architecture enables complex decisions to remain transparent, reproducible, and compliant with institutional and regulatory requirements. A central design principle of AICOS is the concept of Human-Final Authority, ensuring that artificial intelligence systems operate as decision-support mechanisms rather than autonomous decision-makers in environments where accountability and oversight are essential. This work contributes to the emerging field of Decision Intelligence Infrastructure, proposing a new technological category focused on the governance and structure of decision-making processes within advanced digital systems. The architecture is particularly applicable in domains where decision outcomes may involve long-term financial, operational, or societal consequences, including energy infrastructure development, financial risk management, national security systems, and public policy governance. By formalizing the Decision Layer and defining a governance-first architecture for decision systems, AICOS aims to provide a foundational framework for the next generation of accountable AI-assisted decision infrastructures.