All Episodes

Welcome to the ISACA AAISM Audio Course

Episode 90 — Finish strong: lock in governance, risk, and controls for AAISM (Tasks 1–22)

Episode 89 — Exam-day tactics: calm pacing, best-answer logic, and time discipline (Tasks 1–22)

Episode 88 — Final rapid recap: remember the three domains and all 22 tasks (Tasks 1–22)

Episode 87 — Cross-domain practice: choose the right task in realistic scenarios (Tasks 1–22)

Episode 86 — Connect monitoring to incident response so alerts lead to action (Task 16)

Episode 85 — Build continuous monitoring for AI systems, controls, and security signals (Task 12)

Episode 84 — Test robustness and respond when models behave unpredictably (Task 20)

Episode 83 — Improve explainability so decisions are defensible to leaders and auditors (Task 20)

Episode 82 — Review AI outputs for trust and safety without slowing the business (Task 20)

Episode 81 — Design risk-based human oversight so AI stays safe and useful (Task 20)

Episode 80 — Build ethical guardrails that reduce harm while meeting business goals (Task 3)

Episode 79 — Manage privacy requirements across AI inputs, outputs, and user access (Task 3)

Episode 78 — Protect embeddings, prompts, and inference logs as sensitive AI assets (Task 14)

Episode 77 — Control data pipelines with lineage, access control, and secure storage (Task 14)

Episode 76 — Review and tune AI security controls as models, data, and threats change (Task 12)

Episode 75 — Assign control owners and evidence so controls survive real operations (Task 12)

Episode 74 — Apply security controls across the AI life cycle to treat risk (Task 12)

Episode 73 — Validate models for safety, accuracy, and security failure modes (Task 22)

Episode 72 — Secure build, train, and deploy pipelines for repeatable safe releases (Task 22)

Episode 71 — Understand the AI development life cycle from idea to retirement (Task 22)

Episode 70 — Document architecture decisions so governance and audit stay aligned (Task 11)

Episode 69 — Align AI architecture with enterprise identity, network, and data standards (Task 11)

Episode 68 — Integrate AI architecture into enterprise architecture without shadow systems (Task 11)

Episode 67 — Implement AI architecture protections for identity, secrets, and isolation (Task 10)

Episode 66 — Reduce AI attack surface through smart deployment and integration choices (Task 10)

Episode 65 — Design AI security architecture with clear trust boundaries and data flows (Task 10)

Episode 64 — Domain 3 overview: secure AI technologies using architecture and controls (Task 10)

Episode 63 — Domain 2 quick review: risk lifecycle, threats, testing, and vendors (Tasks 4–9)

Episode 62 — Verify vendor AI security through audits, tests, and contract enforcement (Task 9)

Episode 61 — Monitor vendor controls using evidence, updates, and incident notifications (Task 9)

Episode 60 — Embed vendor AI security requirements before procurement begins (Task 9)

Episode 59 — Retest and document fixes so AI vulnerabilities stay closed (Task 7)

Episode 58 — Build AI vulnerability management from discovery to remediation (Task 7)

Episode 57 — Design AI security testing that matches your model, data, and use case (Task 7)

Episode 56 — Build a reassessment cadence that prevents stale AI risk decisions (Task 6)

Episode 55 — Monitor external changes like laws, vendors, and new AI capabilities (Task 6)

Episode 54 — Monitor internal changes that require AI risk reassessment (Task 6)

Episode 53 — Keep threat understanding current as attackers and tools evolve (Task 5)

Episode 52 — Assess AI threats by likelihood and impact, not hype and fear (Task 5)

Episode 51 — Identify the AI threat landscape using realistic abuse cases (Task 5)

Episode 50 — Assign AI risk owners and approvals so accountability is never unclear (Task 4)

Episode 49 — Connect AI risks to enterprise risk reporting and decision-making (Task 4)

Episode 48 — Run the AI risk management life cycle from intake to monitoring (Task 4)

Episode 47 — Domain 2 overview: manage AI risk while enabling business opportunity (Task 4)

Episode 46 — Domain 1 recap drill: pick the right task under pressure (Tasks 1–21)

Episode 45 — Plan for vendor outages and safe degraded modes in AI systems (Task 17)

Episode 44 — Set recovery goals for AI services, data pipelines, and vendors (Task 17)

Episode 43 — Add AI systems to business continuity plans without hidden weak points (Task 17)

Episode 42 — Eradicate root causes and recover safely after AI security incidents (Task 16)

Episode 41 — Notify and escalate during AI incidents with the right triggers (Task 16)

Episode 40 — Contain AI incidents quickly by limiting access and stopping risky flows (Task 16)

Episode 39 — Report AI security incidents on time without losing accuracy (Task 15)

Episode 38 — Document AI incidents clearly for regulators, contracts, and executive updates (Task 15)

Episode 37 — Investigate AI security incidents by collecting the right evidence fast (Task 15)

Episode 36 — Domain 1 quick review: governance, policies, assets, metrics, and training (Tasks 1–3)

Episode 35 — Operationalize tools with tuning, ownership, and measurable outcomes (Task 19)

Episode 34 — Implement AI security tools into monitoring, alerting, and response workflows (Task 19)

Episode 33 — Review AI security tools by coverage, gaps, and operational fit (Task 19)

Episode 32 — Use metrics to prioritize work and prove security program value (Task 18)

Episode 31 — Monitor AI metrics to spot misuse, drift, and early incident signals (Task 18)

Episode 30 — Define AI security metrics leaders can understand and act on (Task 18)

Episode 29 — Build an AI security program that fits the enterprise security program (Task 19)

Episode 28 — Manage retention and deletion to reduce long-term AI data exposure (Task 14)

Episode 27 — Preserve data integrity so models stay reliable and trustworthy (Task 14)

Episode 26 — Protect training and test data with access control and secure storage (Task 14)

Episode 25 — Identify data risks across the AI life cycle: leaks and tampering (Task 14)

Episode 24 — Keep the AI inventory accurate with routine governance checks (Task 13)

Episode 23 — Classify AI assets by sensitivity, criticality, and compliance scope (Task 13)

Episode 22 — Inventory AI assets: models, prompts, data, and key dependencies (Task 13)

Episode 21 — Refresh training when threats, tools, and regulations change (Task 21)

Episode 20 — Build AI security awareness training that sticks in daily work (Task 21)

Episode 19 — Create acceptable use guidelines that reduce risky AI behavior (Task 21)

Episode 18 — Essential Terms: Plain-Language Glossary for fast, accurate recall (Tasks 1–22)

Episode 17 — Keep AI security policies current using ownership and change control (Task 2)

Episode 16 — Turn policies into standards, guidelines, and step-by-step procedures (Task 2)

Episode 15 — Write AI security policies people can follow without guessing (Task 2)

Episode 14 — Prove conformity by building defensible evidence for regulators and contracts (Task 8)

Episode 13 — Perform AI impact assessments with scope, evidence, and actionable results (Task 8)

Episode 12 — Plan AI impact assessments early so compliance is not an afterthought (Task 8)

Episode 11 — Translate AI regulations into practical, testable security requirements (Task 3)

Episode 10 — Apply ethical principles when AI outcomes create real business risk (Task 3)

Episode 9 — Use industry frameworks to organize AI governance and security work (Task 3)

Episode 8 — Set governance routines that keep AI security decisions consistent (Task 1)

Episode 7 — Define AI roles and responsibilities so decisions are owned and clear (Task 1)

Episode 6 — Build an AI governance charter that aligns to business objectives (Task 1)

Episode 5 — Domain 1 overview: lead AI governance and program management confidently (Task 1)

Episode 4 — Exam Acronyms: High-Yield Audio Reference for AAISM daily practice (Tasks 1–22)

Episode 3 — Walk through an AI system life cycle in clear, simple language (Task 22)

Episode 2 — Understand how AAISM questions map to real AI security work (Tasks 1–22)

Episode 1 — Exam orientation and a spoken 30-day plan to pass AAISM (Tasks 1–22)