ARAI offers a suite of certification programs designed to prepare learners, professionals, and organizations to develop, govern, and deploy artificial intelligence responsibly. Each certification aligns with global standards, regulatory frameworks, and emerging best practices in AI governance, ethics, and safety. Our goal is to build a skilled workforce capable of ensuring AI systems are transparent, fair, accountable, and focused on human well-being.
These certifications combine theory, hands-on activities, case studies, and assessment components to ensure participants can apply responsible AI principles in real-world environments.
CRAIP – Certified Responsible AI Practitioner
Core ethics and foundations
Beginner (Entry-Level)
E-HCE – Ethical AI Design & Human-Centered Engineering
Ethical systems + product design
Intermediate
C-AIGCS – AI Governance & Compliance Specialist
Global policy, regulation, oversight
Advanced
CASRMA – AI Safety & Risk Management Analyst
High-risk systems testing and red-teaming
Advanced
To earn a certification, participants must:
These certifications are ideal for:
The future of AI requires leaders who understand not only how systems work—but how they should serve humanity. ARAI certifications prepare learners to lead with integrity, safety, and accountability.
Become certified. Become a leader in ethical AI.

Focus: Foundations of ethical AI, governance frameworks, risk assessment, fairness, transparency, and responsible decision-making.
Ideal For: Analysts, educators, technical teams, and those entering the AI ethics workforce.

Focus: Regulatory compliance frameworks including NIST AI RMF, OECD AI Principles, EU AI Act, ISO/IEC Standards, and accountability structures for AI oversight.
Ideal For: Policy analysts, legal teams, compliance officers, public sector entities, and corporate governance teams.

Focus: Inclusive design, algorithmic fairness, dataset evaluation, human-computer interaction, explainability, and responsible lifecycle deployment.
Ideal For: Developers, product managers, UX/UI designers, and machine learning engineers.

Focus: AI risk modeling, safety testing, harm prevention, red-team evaluations, emergent behavior detection, safety alignment, and responsible deployment standards.
Ideal For: AI researchers, safety engineers, auditors, and advanced risk and oversight teams
We use cookies to analyze website traffic and optimize your website experience. By accepting our use of cookies, your data will be aggregated with all other user data.