AI Frameworks → Business Frameworks

Strong Mappings

COSO ERM: NIST AI RMF's four functions (Govern, Map, Measure, Manage) map directly to COSO ERM's risk identification, assessment, response, and monitoring components. Both treat risk governance as a board-level responsibility.

COBIT: COBIT's governance and management objectives align well with NIST AI RMF. Both address governance structures, stakeholder needs, risk optimization, and resource management — COBIT at the IT level, NIST AI RMF at the AI level.

FAIR: FAIR's quantitative risk analysis methodology directly supports NIST AI RMF's Measure function. FAIR provides the financial quantification that NIST AI RMF calls for but doesn't prescribe.

DMBOK: NIST AI RMF's Map function (understanding AI context and data) directly depends on DMBOK's data governance, quality, and lineage practices. You can't manage AI risk without managing data risk.

ISO 27001: NIST AI RMF's security and resilience requirements map to ISO 27001 controls. Both require risk assessments, control implementation, monitoring, and continuous improvement — ISO 27001 for information security, NIST AI RMF for AI trustworthiness.

Strong Mappings

COSO ERM: EU AI Act's risk classification tiers (unacceptable, high, limited, minimal) directly feed COSO ERM risk assessment processes. Organizations already doing ERM can classify AI systems within their existing risk taxonomy.

COBIT: COBIT's governance and compliance objectives align with EU AI Act's mandatory requirements. COBIT provides the IT governance structure to ensure AI systems meet the Act's documentation, transparency, and oversight requirements.

DMBOK: EU AI Act's requirements for training data quality, bias testing, and data governance directly require DMBOK-level data management practices. You can't comply with the Act's data provisions without mature data management.

Strong Mappings

COSO ERM: ISO 42001's AI management system structure (Plan-Do-Check-Act) integrates naturally with COSO ERM. Both use risk-based approaches with governance, assessment, treatment, and monitoring cycles.

ITIL: ISO 42001 follows the same management system structure as other ISO standards. Organizations already running ITIL-aligned IT service management can extend their service management practices to cover AI management system requirements.

COBIT: Both are governance frameworks with complementary scope. COBIT governs IT broadly; ISO 42001 governs AI specifically. Organizations can nest ISO 42001 AI governance within their COBIT IT governance structure.

DMBOK: ISO 42001 requires data management for AI systems. DMBOK provides the established practices for meeting those requirements. Data governance, quality, and lifecycle management are foundational to ISO 42001 compliance.

ISO 27001: Both are ISO management system standards using the same PDCA structure. Organizations certified in ISO 27001 can extend their ISMS to incorporate ISO 42001 AI management system requirements with significant structural reuse.

Strong Mappings

COSO ERM: Microsoft's Responsible AI Standard requires impact assessments and risk mitigation for AI systems, directly paralleling COSO ERM's risk assessment and response processes. Both emphasize governance structures and accountability.

COBIT: Both are governance-oriented frameworks. Microsoft's six principles (fairness, reliability, privacy, inclusiveness, transparency, accountability) map to COBIT governance objectives with AI-specific requirements.

DMBOK: Microsoft's privacy, fairness, and transparency requirements directly depend on data management practices. Training data quality, bias detection in data, and data provenance tracking require DMBOK-level data management.

Strong Mappings

COSO ERM: Model Risk Management (SR 11-7) IS enterprise risk management applied to models. Model validation, monitoring, and governance are a subset of COSO ERM's risk management processes. Natural structural fit.

COBIT: SR 11-7's governance requirements (model owner, validator, independent review) directly parallel COBIT's IT governance structure. Both require clear roles, documentation, and oversight for technology-driven decisions.

Six Sigma / Lean: SR 11-7's emphasis on model performance measurement, validation testing, and ongoing monitoring directly parallels Six Sigma's statistical rigor. Model validation IS statistical quality control applied to predictive models.

FAIR: SR 11-7 requires model risk quantification. FAIR provides the methodology to quantify that risk in financial terms. FAIR is arguably the best tool for meeting SR 11-7's risk quantification expectations.

DMBOK: Model risk is inseparable from data risk. SR 11-7 requires understanding model inputs, and DMBOK provides the data governance, quality, and lineage practices that make model validation possible.

SOX: When models affect financial reporting (CECL loss estimates, revenue forecasting, asset valuation), SR 11-7 model governance directly supports SOX internal control requirements. The model IS the control.

Strong Mappings

COSO ERM: NIST CSF's five functions (Identify, Protect, Detect, Respond, Recover) are cybersecurity risk management — a direct subset of COSO ERM. Cyber risk IS enterprise risk, and the frameworks nest naturally.

ITIL: NIST CSF's Detect, Respond, and Recover functions align directly with ITIL's incident management, problem management, and IT service continuity management. Security operations run on ITIL processes.

COBIT: NIST CSF's governance-oriented approach aligns with COBIT's IT governance framework. COBIT provides the governance structure; NIST CSF provides the cybersecurity-specific control framework within it.

FAIR: FAIR was originally designed for information risk quantification — the same domain as NIST CSF. FAIR provides the financial quantification methodology for NIST CSF risk assessments.

ISO 27001: NIST CSF and ISO 27001 are the two most widely adopted cybersecurity/information security frameworks globally. They cover the same domain with different structures — NIST CSF is function-based, ISO 27001 is control-based. Highly complementary.