Auditing AI Systems in Critical Sectors

Auditing AI Systems in Critical Sectors

by Prabh Nair

Applied Sciences & Engineering AI & Society UBDigital and Information technology: general topicsUBJDigital and information technologies: social and ethical aspects
🎙 Prabh Nair 👥 184K 📅 July 17, 2026 ⏱ 57 min 👁 4K 📄 expert opinion 🧭 2026-08-16
Available in: English (current) Français

Keywords

AI auditcritical infrastructureISO 42001agentic AIvendor risk

Summary

In this podcast, Prabh Nair interviews Priyank Soni, a cybersecurity and AI governance expert, on auditing AI systems in critical sectors. They discuss how AI auditing differs from traditional IT auditing, emphasizing the challenges of black-box models, agentic AI, and machine-to-machine interactions. Soni highlights the need for new frameworks like ISO/IEC 42001 and the evolution of zero-trust architecture to include AI agents. He stresses the importance of data mapping, inventory, and classification as starting points for AI audits, and warns about supply chain risks, recommending SBOM and ABOM. The conversation covers vendor accountability, the limitations of self-assurance, and the need for continuous monitoring and specialized skills for auditors. Soni notes that AI auditing is still maturing, with global standards emerging but not yet universally adopted. He calls for more trained auditors and proactive regulatory measures, citing examples from Singapore and the EU. The podcast provides practical insights for professionals in cybersecurity, GRC, and audit, emphasizing the need for robust documentation, evidence, and collaboration between auditors, vendors, and internal teams.

169 words

Critical Evaluation

Value of the Information & Strength of the Argument

The value of the information lies in its practical insights from an experienced professional, addressing real-world challenges in AI auditing. The argumentation is coherent and grounded in examples, such as the hesitation of a multinational bank to deploy AI due to accountability concerns, and the analogy of agents for celebrities to explain agentic AI. However, some arguments rely on anecdotal evidence and lack rigorous empirical support. The discussion on standards like ISO 42001 and SBOM is relevant, but the depth is limited, and the reasoning sometimes jumps between topics without deep elaboration.

Scientific Rigor, Source Quality, Title Accuracy

The scientific rigor is moderate; the content is based on expert opinion rather than peer-reviewed research. The quality of sources is limited, with only a LinkedIn profile provided, and no direct citations to standards or studies. The title accurately reflects the content, which focuses on auditing AI in critical sectors. The discussion references ISO 42001, SBOM, and CERT advisories, but without specific URLs or detailed references. The adequacy between title and content is good, as the podcast directly addresses the topic.

188 words

Title / Content Match

The title accurately reflects the content, which focuses on auditing AI systems in critical sectors, discussing challenges, standards, and practical approaches.

Quality & Reliability

7/10

The content is based on the expert opinion of Priyank Soni, a cybersecurity and AI governance leader, and covers current standards and practices. However, it lacks detailed citations and empirical evidence, and some claims are anecdotal.

Chapters

Cited Sources

  • Priyank Soni LinkedIn Profile — Guest's professional profile, providing credentials and background.

Concurring Sources

  • ISO/IEC 42001 — Referenced as a key standard for AI governance and auditing.
  • CISA SBOM — Relevant to supply chain security and SBOM usage mentioned in the podcast.

Contribution & Novelties

The podcast provides a practical overview of AI auditing challenges and approaches, particularly in critical sectors. It emphasizes the shift from traditional IT auditing to AI-specific considerations, such as black-box models and agentic AI. The discussion on SBOM and ABOM highlights emerging practices. However, the content is not highly novel, as similar topics are covered in industry discussions.

Pour aller plus loin :

  • ISO/IEC 42001 - AI management systems — Official standard for AI management systems, relevant to AI governance and auditing.
  • Software Bill of Materials (SBOM) — CISA’s page on SBOM, relevant to supply chain security in AI systems.
  • NIST AI Risk Management Framework — Framework for managing AI risks, relevant to AI auditing practices.

116 words

Radar Profile

The radar profile shows balanced scores across all dimensions, with slightly higher scores in quantity and reliability, indicating a solid but not exceptional content. The technical level is moderate, making it accessible to a broad professional audience.

Reliability 7/10

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