Page 29 - The Annual AI Governance Report 2025 Steering the Future of AI

The Annual AI Governance Report 2025: Steering the Future of AI

Red-Teaming: Red-teaming is a structured process where expert teams simulate adversarial
attacks and real-world threat scenarios against AI systems to identify vulnerabilities, test limits,
and enhance resilience. Unlike traditional testing, red-teaming adopts the perspective of
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potential attackers, probing for weaknesses such as harmful outputs, bias, data leaks, or system
manipulation. Red-teaming is now recognized as essential for AI deployed in critical sectors—
finance, healthcare, infrastructure—where failure could have severe consequences.

Adversarial Testing and Continuous Risk Assessment: Adversarial testing, a core component of
red-teaming, involves designing challenging inputs—such as nonsensical prompts or attempts
to bypass safety guardrails—to expose flaws in AI models. This approach uncovers issues like
bias, harmful content, and security vulnerabilities before deployment, ensuring models are
robust under unpredictable, real-world conditions.

Global Collaboration and Tool for Safety Evaluation: The UK’s AI Security Institute has
launched the Inspect evaluations platform, making advanced safety testing tools available
to the international community and accelerating the adoption of consistent safety standards
worldwide.
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4.5 Certification and Accreditation Programs

Practitioner Certification Pathways: A wide array of AI practitioner certifications now exists,
targeting different expertise levels and career paths. The Certified Artificial Intelligence
Practitioner (CAIP) is a cross-industry certification accredited under ISO/IEC 17024:2012,
emphasizing practical skills in AI and machine learning for system design, implementation,
and deployment. Alongside CAIP, globally recognized certifications such as the Certified
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Artificial Intelligence Scientist (CAIS), ARTIBA AI Certification, and platform-specific credentials
like the Microsoft Azure AI Engineer Associate and NVIDIA Jetson AI Certification support the
development of both foundational and advanced AI competencies across diverse technological
environments. These certifications are designed to validate not only technical proficiency but
also understanding of ethical, legal, and governance aspects of AI, reflecting the growing
demand for responsible practitioners.

Accreditation Programs for AI Systems in Key Sectors: New sector-specific accreditation
initiatives are emerging, such as the URAC Health Care AI Accreditation (launching Q3 2025),
which will provide a verifiable framework for safe, ethical, and equitable AI implementation in
clinical environments. In education, the Global AI Ethics in Education Charter (2025) led by
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UNESCO and partners, is establishing standardized codes of ethics for AI use in academia, with
accreditation agencies encouraged to align local standards with this global charter.
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101 Wisbey, O. (2024, November 21). What is AI red teaming? Search Enterprise AI.
102 Department for Science, Innovation and Technology. (2024, May 10). AI Safety Institute releases new AI
safety evaluations platform. GOV.UK.
103 Certified Artificial Intelligence Practitioner - CAIP Training - CerTNexus. (2025, March 14). CertNexus.
104 URAC to launch First-Ever Health Care AI Accreditation Program in Q3 2025. (2025, May 19). URAC.
105 International Education Accreditation Council. (2025, May 6). Accrediting Ethical AI Integration in Higher
Education: A Roadmap. https:// www .ieac .org .uk/ 46 -Accrediting -Ethical -AI -Integration -in -Higher -Education
-A -Roadmap -blog .php.

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