Ibrahim Waziri Jr.
Ibrahim Waziri Jr. is a Global Insider Risk Lead within Google's Cloud CISO Risk & Compliance Insider Threat team, where he leads initiatives for insider risk management and global cybersecurity regulatory governance. He is also a Cybersecurity Fellow at New America. His work, once focused on U.S. Government national security cloud engineering, now centers on advancing global cybersecurity governance, responsible AI, and digital trust. His expertise spans cybersecurity engineering, national security strategy, product development, responsible AI, and security governance, risk, and compliance (GRC).
Prior to Google, he was a Principal Security Product Manager at Microsoft, leading cybersecurity and AI engineering initiatives, product development, regulatory compliance, and incident management for Microsoft Azure for U.S. national security. He was also an Adjunct Professor of Cybersecurity at Marymount University. His previous experience includes roles at Deloitte Government Public Service (GPS), Apogee Research, Dell-EMC RSA Security, and the U.S. International Trade Commission (USITC). He currently serves on nonprofit boards dedicated to advancing cybersecurity and education. He holds a Ph.D. in Information Security from Purdue University.
Prior to Google, he was a Principal Security Product Manager at Microsoft, leading cybersecurity and AI engineering initiatives, product development, regulatory compliance, and incident management for Microsoft Azure for U.S. national security. He was also an Adjunct Professor of Cybersecurity at Marymount University. His previous experience includes roles at Deloitte Government Public Service (GPS), Apogee Research, Dell-EMC RSA Security, and the U.S. International Trade Commission (USITC). He currently serves on nonprofit boards dedicated to advancing cybersecurity and education. He holds a Ph.D. in Information Security from Purdue University.
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GovSCH: An Open-Source Schema for Authoring Cybersecurity and AI Governance Documents
New America, New America (2025)
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The increasing complexity of cybersecurity and artificial intelligence (AI) executive orders, frameworks, and policies has made translating high-level directives into actionable implementation a persistent challenge. Policymakers, framework authors, and engineering teams often lack a unified approach for interpreting and operationalizing these documents, resulting in inefficiencies, misalignment, and delayed compliance. While existing standards such as the Open Security Controls Assessment Language (OSCAL) address control-level specifications, no standardized, machine-readable format exists for authoring and structuring high-level governance documents. This gap hinders collaboration across disciplines and obscures critical directives’ underlying intent and rationale.
This report introduces Governance Schema (GovSCH), an open-source schema designed to standardize the authoring and translation of cybersecurity and AI governance documents into a consistent, machine-readable format. By analyzing prior executive orders, regulatory frameworks, and policies, GovSCH identifies common structures and authoring practices to create an interoperable model that bridges policymakers, regulatory framework authors, and engineering teams. This approach enables more precise articulation of policy intent, improves transparency, and accelerates the technical implementation of regulations. Ultimately, GovSCH aims to enhance collaboration, standardization, and efficiency in cybersecurity and AI governance.
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