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IBM AI Governance, Risk & Compliance interview questions

AI Governance, Risk & Compliance is a core part of the IBM AI Security Engineer loop. AI risk frameworks, AI security posture management (AI-SPM), data and tool inventories, control evidence and compliance reporting. Review vendor and acquisition risk with scoped authority, accountable exceptions and explicit assessment gaps. Questions tagged to IBM come first. After them, the top-voted questions from the AI Governance, Risk & Compliance track. Each answer reasons the way a senior security engineer would in front of a panel: attacker, asset, control, and where the control breaks.

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AI Governance, Risk & Compliance questions tagged to IBM

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More AI Governance, Risk & Compliance questions for IBM's loop

Sorted by reader votes. These are not tagged to IBM; they cover the ai governance, risk & compliance ground its AI Security Engineer loop is known to test.

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Concepts behind IBM's AI Governance, Risk & Compliance round

The background these answers assume. Introductory lessons are free; advanced ones need Premium.

Foundational
The NIST AI Risk Management FrameworkThe NIST AI Risk Management Framework (AI RMF 1.0, January 2023) is a voluntary framework for managing risks from AI systems across their lifecycle. It organises the work into four functions: Govern (culture, policy, roles), Map (context and risks of each system), Measure (analysis and testing) and Manage (prioritising and treating risks). It describes characteristics of trustworthy AI, including security and resilience, and has companion profiles such as the Generative AI Profile (NIST AI 600-1). It does not certify anything; its value is a shared structure that engineering controls can hang from.
Foundational
The EU AI Act for EngineersThe EU AI Act regulates AI systems by risk. A short list of practices is prohibited; high-risk systems, such as those used in employment, credit, education or critical infrastructure, must meet requirements including risk management, data governance, logging, human oversight, accuracy, robustness and cybersecurity; some systems carry transparency duties; and providers of general-purpose AI models have their own obligations. It applies to providers and deployers outside the EU when their systems are used in the EU. Dates have shifted: the 2026 Digital Omnibus moved most high-risk deadlines to December 2027 and August 2028.
Foundational
ISO/IEC 42001ISO/IEC 42001:2023 specifies requirements for an AI management system: the policies, roles, processes and controls an organisation uses to develop, provide or use AI responsibly. It follows the same structure as ISO/IEC 27001, so organisations with an information security management system can extend it. It requires AI risk assessment and AI system impact assessment, includes a reference set of controls, and is certifiable by accredited bodies. Certification shows a functioning management system, not that every AI system is safe or legally compliant.
Core
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Assessing an AI System's RiskA practical AI risk assessment turns frameworks into a repeatable intake: register the use case, ask a small set of questions that decide risk (purpose and affected people, data, autonomy and actions, exposure to untrusted input, model source, regulatory category), assign a tier, apply the controls that tier requires, and record owners, residual risk and review dates. Done well, it is fast for low-risk uses and thorough for high-risk ones, and it produces the evidence that the NIST AI RMF, ISO/IEC 42001 and the EU AI Act all ask for.
Foundational
AI Security Posture Management and AI Asset InventoryAI-SPM connects AI assets to data, identities, tools and deployment controls. Build an inventory that supports security decisions without confusing discovered AI usage with verified resistance to prompt injection.
Foundational
Security Control Evidence and Compliance ReportingBuild compliance reports from scoped observations, control ownership and exceptions. Preserve the difference between a passing technical check, effective operation over time and an audit conclusion.
Core
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Security Integration After an AcquisitionIntegrate an acquired company through verified ownership, bounded identity and network trust, data handling and evidence collection. Use discovery and posture tools to inform each step without granting blanket access.
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IBM AI GOVERNANCE, RISK & COMPLIANCE FAQ
What AI Governance, Risk & Compliance questions does IBM ask in interviews?▲

IBM's AI Security Engineer loop draws ai governance, risk & compliance questions such as "What do the UK AI cyber security code, ETSI's AI baseline standard and NIST's draft Cyber AI Profile ask for, and how would you use them?", "Compare the NIST AI RMF, ISO/IEC 42001 and the EU AI Act. Does one satisfy another?", "What are the EU AI Act risk tiers, and what must a high-risk provider do?". AI risk frameworks, AI security posture management (AI-SPM), data and tool inventories, control evidence and compliance reporting. Review vendor and acquisition risk with scoped authority, accountable exceptions and explicit assessment gaps. Every question in the topic is listed below from easiest to hardest, each with a worked answer.

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