The paper introduces the NebuBot® Dual Trust™ AI Gateway Architecture, a privacy-preserving enterprise artificial intelligence governance framework designed to enable organizations to use advanced AI technologies while maintaining strict control over sensitive information, regulatory obligations, and organizational accountability. The proposed architecture combines cryptographic isolation, tokenization, dual-zone processing, human oversight mechanisms, and governance controls to reduce the risks associated with exposing confidential data to external AI systems. The framework is intended for organizations operating in highly regulated environments, including healthcare, financial services, legal services, government, defense, and critical infrastructure sectors. The publication examines enterprise AI governance challenges, evaluates limitations of existing governance approaches, presents the Dual Trust™ framework, and maps the architecture to internationally recognized standards and regulatory frameworks, including ISO/IEC 42001, ISO/IEC 27001, ISO/IEC 27701, NIST AI RMF, NIST SP 800-207, OECD AI Principles, UNESCO AI Recommendations, and the European Union AI Act. This working paper is intended for executives, governance professionals, auditors, regulators, cybersecurity specialists, AI practitioners, researchers, and policy makers seeking practical approaches to responsible and trustworthy enterprise AI deployment. Author: Celso Alvarado, MSc, Ph.D.ORCID: 0000-0003-2826-6217 Series: Nebusis Artificial Intelligence Governance Working Paper SeriesWorking Paper: WP-2026-006Year: 2026 Keywords: Artificial Intelligence Governance, Enterprise AI, Privacy-Preserving AI, Human-in-the-Loop, AI Compliance, AI Risk Management, ISO/IEC 42001, NIST AI RMF, Data Sovereignty, AI Assurance.
Celso Alvarado Martinez (Sun,) studied this question.