Certified Zero-Trust AI Governance Professional (CZTAGP) Certification Program by Tonex
This program equips compliance officers, risk managers, and AI governance leaders to operationalize Zero-Trust across AI assurance, auditing, and oversight. You will learn to design governance models that continuously verify identities, data sources, model behaviors, and API interactions while maintaining traceability and accountability.
The curriculum aligns with NIST AI RMF, ISO/IEC 42001, and the EU AI Act, translating policies into measurable controls, risk signals, and attestations. Cybersecurity impact is central as you implement least privilege, micro-segmentation, and continuous monitoring to harden AI pipelines and interfaces. By the end, you can produce defensible evidence for audits, sustain policy-driven guardrails, and maintain trustworthy, compliant AI at scale within complex enterprises where cybersecurity and governance converge.
Learning Objectives
- Develop Zero-Trust aligned AI governance operating models
- Map NIST, ISO/IEC 42001, and EU AI Act requirements to control catalogs
- Define trust metrics, KPIs, and risk thresholds for AI systems
- Implement continuous verification of data lineage, model behavior, and APIs
- Establish audit trails, attestations, and evidence management workflows
- Operationalize policy as code and automate governance checkpoints
- Strengthen cybersecurity by embedding least privilege and continuous monitoring
Audience
- Compliance Officers
- Risk Managers
- AI Governance Professionals
- Data Protection Officers
- AI/ML Engineers and MLOps Leads
- Enterprise Architects
- Cybersecurity Professionals
Course Modules
Module 1: AI Governance and Compliance Foundations
- Governance models and operating structures
- NIST AI RMF core functions in practice
- ISO/IEC 42001 management system essentials
- EU AI Act obligations and risk tiers
- Roles, RACI, and accountability mapping
- Control baselines and policy hierarchies
Module 2: Trust Metrics and Risk KPIs
- Defining trust signals and thresholds
- Model performance, robustness, and drift KPIs
- Data quality, lineage, and provenance metrics
- Third-party and API risk indicators
- Risk registers and scoring methods
- Dashboarding, alerts, and escalation paths
Module 3: Continuous Auditing and Attestation
- Evidence collection and immutable logs
- Attestation schemas and assurance levels
- Sampling strategies and audit playbooks
- Automated control testing pipelines
- Non-conformance tracking and CAPA
- Regulator-ready reporting packages
Module 4: Zero-Trust AI Security Policy Management
- Identity, device, and workload verification
- Least privilege for models and services
- Network micro-segmentation for AI traffic
- Policy as code for guardrails and gates
- Secrets, keys, and credential governance
- Runtime monitoring and response triggers
Module 5: Governance Integration Across AI Lifecycle
- Ideation and use-case risk triage
- Data acquisition and consent controls
- Model design reviews and hazard analysis
- Pre-deployment validation and sign-offs
- Release checklists and change control
- Post-deployment monitoring and rollback
Module 6: Assurance Reporting and Stakeholder Oversight
- Executive scorecards and board briefings
- Regulator and auditor communications
- Vendor and third-party assurance reviews
- SLA, SLO, and compliance attestations
- Incident postmortems and lessons learned
- Program maturity roadmaps and benchmarking
Exam Domains
- Zero-Trust Principles for AI Control Design
- Regulatory Alignment and Control Mapping
- Trust Metrics, KPIs, and Risk Scoring
- Continuous Audit, Evidence, and Attestation
- Policy as Code and Automated Governance
- Stakeholder Reporting and Assurance Strategy
Course Delivery
The course is delivered through a combination of expert-led lectures, interactive discussions, structured workshops, and project-based learning focused on Certified Zero-Trust AI Governance Professional. Participants gain access to curated online resources, case studies, templates, and practical tools to apply concepts to their organizational context.
Assessment and Certification
Participants are assessed through quizzes, assignments, and a capstone project demonstrating end-to-end Zero-Trust AI governance. Upon successful completion, participants receive the Certified Zero-Trust AI Governance Professional (CZTAGP) certificate from Tonex.
Question Types
- Multiple Choice Questions (MCQs)
- Scenario-based Questions
Passing Criteria
To pass the Certified Zero-Trust AI Governance Professional (CZTAGP) Certification Training exam, candidates must achieve a score of 70% or higher.
Ready to embed Zero-Trust in your AI governance Playbook Join the CZTAGP program by Tonex to build compliant, resilient, and cybersecurity-driven AI operations at scale. Enroll today and elevate your organization’s AI assurance.