How IBAI Evaluates, Verifies & Approves AI Providers, Training Programs,

Professional Institutes, and Business Entities 

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The IBAI™ Accreditation Process is designed to protect the quality, safety, and global integrity of professional AI education. Every program seeking IBAI’s seal must complete the following structured, transparent, and ethical review pathway.  Accreditation with IBAI is not a simple application, it is a globally recognized evaluation of compliance, ethics, curriculum quality, instructional integrity, and real-world alignment with international standards. Training Provider accreditation confirms who you are. Program accreditation confirms what you teach. IBAI evaluates both - separately and responsibly.

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• Providers are accredited for capability and governance

• Programs are accredited for quality and compliance

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This separation protects learners, providers, and the global credibility of IBAI-approved education.

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• Organizational ATP or Trainer ATP accreditation is mandatory before any program, course, event, conference, or seminar may be submitted for IBAI Program Accreditation.  Programs are accredited individually, even when delivered by an IBAI-accredited organization or trainer. 

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• Accreditation at the provider or trainer level does not automatically accredit programs. This structure ensures that who is delivering the training and what is being delivered are both evaluated independently and responsibly. ​Training Provider accreditation does NOT automatically accredit all programs. Each course or program must be submitted and evaluated individually. Accreditation is earned through preparation, alignment, and compliance, not sales or status. Providers who follow IBAI’s preparation guide and course blueprint have substantial approval odds, provided standards are met. 

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IBAI AEF™ - Accreditation Evaluation Framework

All IBAI accreditations are evaluated using the AEF™, ensuring consistent, ethical, and globally aligned review.

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IBAI evaluates whether an organization, trainer, or program demonstrates:

• Accountability & Governance - Clear ownership, responsibility, and ethical oversight

• Ethical & Responsible AI Alignment - Transparent, responsible, and ethical AI use or representation

• Fit-for-Purpose Design - Appropriate structure and delivery aligned with the stated purpose

• Measurable Outcomes - Clear, realistic, and verifiable learning or value outcomes

• Transparency & Representation - Accurate claims and proper use of accreditation status

• Participant & Learner Protection - Clear expectations, disclosures, and professional conduct

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