Certified AI Regulatory & Legal Specialist (CAIRLS) Certification Program by Tonex
The CAIRLS program prepares legal, policy, and regulatory professionals to govern AI responsibly across jurisdictions. Participants learn how to interpret, compare, and operationalize leading AI frameworks, including EU, U.S., China, UAE, and OECD approaches. The focus is applied. You will translate rules into controls, evidence, and contracts that withstand scrutiny.
The program emphasizes governance that accelerates innovation while reducing risk and cost. You will practice drafting policies, performing regulatory impact assessments, and aligning procurement with compliance obligations.
Cybersecurity is integral. You will map AI requirements to security controls, incident reporting duties, and cross-border transfer constraints. You will connect AI risk tiers to secure-by-design patterns, model assurance, and vendor oversight. Graduates can brief executives, advise product teams, and negotiate defensible terms with regulators and partners.
Learning Objectives:
- Compare global AI laws and directives.
- Design governance for risk-tiered AI systems.
- Conduct Regulatory Impact Assessments (RIA).
- Align privacy, security, and model controls.
- Draft AI policies, notices, and contracts.
- Prepare evidence for audits and inquiries.
Audience:
- Legal and Compliance Professionals
- Policy Makers and Regulators
- Data Protection Officers and Privacy Counsels
- Risk and Governance Leaders
- Product and AI Program Managers
- Cybersecurity Professionals
Program Modules:
Module 1: Comparative Global AI Frameworks
- Scope, definitions, and risk tiers
- High-risk obligations and conformity
- Foundation model and provider duties
- Enforcement, penalties, and appeals
- Timelines and phased obligations
- Extraterritorial reach and conflicts
Module 2: Data Protection and Privacy in AI
- Lawful basis, transparency, and notices
- DPIA/RIA for training and deployment
- De-identification and data minimization
- Cross-border transfers and safeguards
- Rights requests and model explainability
- Children’s data and dark patterns
Module 3: IP, Content, and Model Governance
- Training data copyright and TDM limits
- Licensing, provenance, and dataset terms
- Output ownership and infringement risk
- Watermarking, labeling, and disclosures
- Open-source and third-party components
- UGC moderation and safe-harbor strategy
Module 4: Liability, Safety, and Assurance
- Product liability and negligence theories
- Duty of care and foreseeable misuse
- Safety cases and assurance artifacts
- Incident reporting and response plans
- Harm evaluation and redress pathways
- Insurance and indemnity positioning
Module 5: RIA and Compliance Operations
- RIA scoping and methodology
- Control mapping to policies and standards
- Evidence plans and document retention
- KPIs, KRIs, and governance dashboards
- Continuous monitoring and updates
- Internal reviews and executive sign-off
Module 6: Contracts, Procurement, and Oversight
- AI clauses and allocation of risk
- Vendor diligence and third-party attestations
- DPAs, SCCs, and cross-border terms
- Service levels, guardrails, and kill-switches
- Human oversight and role definitions
- Training, change management, and audits
Exam Domains:
- Global AI Law and Policy Analysis
- Data Governance and Privacy Controls
- IP, Content, and Model Provenance
- AI Risk, Safety, and Incident Governance
- Compliance Operations and Audit Readiness
- Contracts, Procurement, and Organizational Oversight
Course Delivery:
The course combines expert-led lectures, interactive discussions, case studies, and drafting workshops. Participants access curated online resources, readings, templates, and practical tools to apply concepts to real programs.
Assessment and Certification:
Assessment includes quizzes, short assignments, and a capstone RIA and policy bundle. Upon successful completion, participants receive the CAIRLS Certificate by Tonex.
Question Types:
- Multiple Choice Questions (MCQs)
- Scenario-based Questions
Passing Criteria:
To pass the CAIRLS Certification Training exam, candidates must achieve a score of 70% or higher.
Ready to lead AI governance with confidence? Enroll today to formalize your expertise and equip your organization for accountable, secure AI at scale.