Global AI Bot Identity, Governance, Control, Security & Risk-Mitigation Framework

A Proposed National and Global Identification, Accountability and Lifecycle Management Framework for Present and Future AI Systems Research Paper / 184th Tech-Focused Idea Author: Muhammad Asim – Global Progress VolunteerORCID: 0000-0002-8575-4447Date: 13 November 2026Status: Original Proposed Conceptual Framework DOI: 10.5281/zenodo.24194956 / Abstract Artificial Intelligence (AI) bots, autonomous agents and intelligent software systems are increasingly becoming part of personal, commercial, industrial, governmental and international activities. Their growing capabilities, autonomy, connectivity and access to digital resources introduce new requirements for identification, authorization, security, accountability, monitoring and risk management. This research proposes a Global AI Bot Identity, Governance, Control, Security & Risk-Mitigation Framework (GAIB-GCSRM), designed to establish a structured identification and governance ecosystem for AI bots operating within national and international digital environments. The proposed framework introduces AI-specific national and global identification mechanisms, supported by operational credentials, ownership and responsibility records, authentication, access permissions, risk classification, monitoring, auditability, emergency intervention and lifecycle management. Unlike human identification systems, the proposed AI identification architecture is not intended to establish human-like citizenship, nationality rights, passports, visas or other human identity entitlements. Its purpose is to identify, authenticate, govern and manage AI systems according to their technical characteristics, operational roles, authorization levels and associated responsibilities. The framework also considers future AI developments, including autonomous agents, interconnected AI ecosystems, advanced robotics and AI systems capable of performing increasingly complex tasks. The ultimate objective is to propose a scalable, interoperable, privacy-conscious and future-ready global approach for responsible AI identification and governance.