Naresh Thalla Mudhiraj
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AAIA

ISACA · AI Audit

AAIA - ISACA Advanced in AI Audit

Advanced (add-on)Active - launched May 2025

Experienced IT auditors and advisors who assess, implement or audit AI systems and want to show AI audit expertise on top of CISA (or an equivalent audit/accounting designation).

Overview

Prerequisites
Must hold an active CISA, or one of the listed designations with an IT audit/advisory focus (e.g., CIA, US CPA, ACCA/FCCA, Canadian/Australian/Japanese CPA, ICAEW ACA/FCA, CA ANZ, HKICPA). US$50 application fee after passing.
Maintenance
ISACA Advanced-certification policy: at least 10 CPE hours a year and 30 over a 3-year cycle in the AI specialty, keep the prerequisite certification active, and pay one annual maintenance fee of US$20 (members) / US$35 (non-members) that covers all ISACA Advanced certifications held.
Outline in effect
check official site

Exam facts

Questions
90
Duration
2.5 hours (150 minutes)
Question types
Multiple choice, one best answer
Passing score
450 on a 200-800 scaled score
Format
Linear, computer-based
Delivery
PSI test centres or remote proctoring (test centre only for residents of India, mainland China and Hong Kong)

Cost

Member
US$459
Non-member
US$599
Notes
Plus US$50 application fee.

Domains & weights

  1. Domain 1 - AI Governance and Risk33%
  2. Domain 2 - AI Operations46%
  3. Domain 3 - AI Auditing Tools and Techniques21%

Upcoming changes

No announced changes as of 19 Oct 2026.

Study plan 8 weeks · 5-7 hrs/week

  1. Week 1

    Domain 1

    • AI model types, governance programme, AI risk management, privacy/data governance, ethics, regulation and standards (EU AI Act, NIST AI RMF, ISO/IEC 42001).
  2. Week 2

    Domain 2 (part 1)

    • Data management for AI, development methodologies and life cycle, AI-specific change management.
  3. Week 3

    Domain 2 (part 2)

    • Supervising AI outputs/impacts, testing techniques, AI threats and vulnerabilities (prompt injection, poisoning, model theft), AI incident response.
  4. Week 4

    Domain 3

    • Audit planning for AI, testing and sampling, evidence, data quality/analytics, AI audit reporting; using AI tools in the audit itself.
  5. Week 5

    CISA concepts applied to AI

    • Revisit governance, change management, third-party and BCM controls and restate them for AI systems and AI vendors.
    • Do 60 mixed questions; note every miss caused by answering as a technologist instead of an auditor.
  6. Week 6

    Case study: audit an AI use case

    • Pick a real AI use case (e.g., a credit-scoring model or a GenAI chatbot) and draft an audit plan, risk-control matrix and test steps.
    • Identify the evidence you would request: model cards, data lineage, validation results, change logs, monitoring reports.
  7. Week 7

    Practice

    • ISACA free practice exam and QAE database; timed 90-question mock in 150 minutes.
  8. Week 8

    Review

    • Focus on Domain 2 (46%); re-read missed explanations.

Exam tips

  • Read every question for the role you are playing (auditor, risk practitioner, security manager): ISACA rewards the answer that fits that role, not the most technical one.
  • Watch qualifier words such as FIRST, BEST, MOST, PRIMARY and GREATEST: several options are often true, and only one is the best next step.
  • There is no penalty for wrong answers, so never leave a question blank.
  • You have about 1.6 minutes per question (90 in 150 minutes).

Common pitfalls

  • Answering as a data scientist rather than an auditor.
  • Under-studying AI Operations, the largest domain (46%).
  • Forgetting the prerequisite must stay active to keep AAIA.

Resources & official links

Official

Also widely used

  • NIST AI RMF 1.0 / AI 600-1
  • ISO/IEC 42001 and 42005
  • OWASP Top 10 for LLM Applications
  • IIA AI Auditing Framework

Sources

Last verified 19 Oct 2026. Values marked “check official site” could not be confirmed from an official source.

Practice questions original questions · pick an answer or reveal it

An IS auditor is asked to audit a newly deployed AI credit-scoring model. What should the auditor do FIRST?

Domain 3

Which evidence BEST shows that an AI model was validated before release?

Domain 2

Data poisoning attacks target which stage?

Domain 2

Which control MOST directly reduces prompt-injection risk in an LLM application?

Domain 2

Who should own the risk of an AI system used in a business process?

Domain 1

Model drift is BEST detected by:

Domain 2

An auditor uses a generative AI tool to summarise interview notes. What is the GREATEST concern?

Domain 3

Which is the BEST way for an auditor to test fairness of an AI hiring model?

Domain 3

Changes to a production AI model should be governed by:

Domain 2

Which framework element MOST supports accountability for AI decisions?

Domain 1

Related topics in the question bank

Next upStudy with scenario flashcards