Master of AI Leadership and Governance (MAILG) Certification Program by Tonex
MAILG by Tonex equips leaders to architect trustworthy AI programs that align innovation with organizational strategy and measurable value. The program blends executive level governance frameworks, risk mitigation, and ethical decision making with practical implementation toolkits.
Cybersecurity is treated as a board level priority ensuring AI systems protect data integrity, confidentiality, and availability. Participants learn how cybersecurity controls intersect with AI pipelines to prevent model abuse and adversarial threats. Robust cybersecurity posture is embedded across policies, metrics, and lifecycle management.
Learning Objectives
- Lead enterprise AI strategy that aligns with mission and KPIs
- Establish accountable governance with clear roles and decision rights
- Operationalize responsible AI ethics through policies and audits
- Build risk registers and mitigate regulatory exposure across jurisdictions
- Design measurement systems for value realization and portfolio health
- Strengthen cybersecurity resilience across AI data, models, and endpoints
- Communicate AI outcomes to executives, boards, and regulators
Audience
- Executives and Business Leaders
- Product and Program Managers
- Data and AI Leaders
- Governance Risk and Compliance Professionals
- Cybersecurity Professionals
- Enterprise Architects and Solution Owners
- Policy and Legal Counsel
Course Modules
Module 1: Strategic AI Foundations
- AI vision and operating model
- Value cases and portfolio mapping
- Stakeholder alignment and sponsorship
- Funding models and guardrails
- Maturity assessment and roadmaps
- Change management essentials
Module 2: Governance and Accountability
- Roles charters and RACI
- Policy hierarchy and harmonization
- Decision gates and signoffs
- Model cards and documentation
- Third party and vendor oversight
- Audit readiness and evidence
Module 3: Risk and Compliance
- Enterprise risk taxonomy
- Regulatory landscape scanning
- Impact assessments and DPIA
- Controls library and testing
- Incident response and playbooks
- Monitoring and continuous assurance
Module 4: Data and Model Stewardship
- Data provenance and lineage
- Quality standards and curation
- Model lifecycle oversight
- Drift detection and retraining
- Transparency and explainability
- Access and entitlement hygiene
Module 5: Security by Design
- Threat modeling for AI
- Secure development practices
- Adversarial robustness testing
- Secrets and key management
- Security monitoring and SIEM use
- Business continuity and recovery
Module 6: Value Realization and Scaling
- Success metrics and KPIs
- Benefit tracking and reporting
- Platform and reuse patterns
- Operating cadence and forums
- Vendor and ecosystem strategy
- Scale up and sustainment plans
Exam Domains
- AI Strategy and Leadership
- Governance Frameworks and Oversight
- Risk Management and Compliance
- Data and Model Stewardship Principles
- Security and Resilience for AI Systems
- Value Measurement and Program Scaling
Course Delivery
The course is delivered through a combination of lectures, interactive discussions, hands-on workshops, and project-based learning, facilitated by experts in the field of Master of AI Leadership and Governance. Participants will have access to online resources, including readings, case studies, and tools for practical exercises.
Assessment and Certification
Participants will be assessed through quizzes, assignments, and a capstone project. Upon successful completion of the course, participants will receive a certificate in Master of AI Leadership and Governance.
Question Types
- Multiple Choice Questions MCQs
- Scenario-based Questions
Passing Criteria
To pass the Master of AI Leadership and Governance Certification Training exam, candidates must achieve a score of 70% or higher.
Ready to lead trustworthy, secure, and high impact AI at scale Join the MAILG Certification Program by Tonex and transform your organization’s AI future. Enroll today.