AIUC-1 operationalizes emerging AI frameworks

AIUC-1 is designed to be:

Customer-focused. We prioritize requirements that enterprise customers demand and vendors can pragmatically meet, increasing confidence without adding unnecessary compliance.
Adaptable. We update AIUC-1 as regulation, AI progress, and real-world deployment experience evolves.
Transparent. We keep a public change log and share our lessons.
Forward-looking. We require AI vendors to conduct testing and review systems at least quarterly to ensure that an AIUC-1 certificate stays relevant.
Insurance-enabling. We emphasize the risks that lead to direct harms and financial losses.
Predictable. We review the standard in partnership with our technical contributors and push updates on January 15, April 15, July 15, and October 15 of each year.

In practice, this means that AIUC-1 builds on other AI frameworks including the EU AI Act, the NIST AI RMF, ISO 42001, MITRE ATLAS, CSA AICM, and the OWASP Top 10 for agentic AI.

AIUC-1 does not duplicate the work of non-AI frameworks like ISO 27001 or GDPR. AIUC-1 complements SOC 2 and is now offered together by the AICPA as a joint offering.

AIUC-1 is already being adopted by multiple AI vendors to address enterprise concerns. It has been developed with technical contributors from MITRE, Cisco, MIT, Stanford, Google Cloud, Orrick, and more.

AIUC-1 is built on	AIUC-1 does not duplicate
EU AI Act NIST AI RMF ISO 42001 MITRE ATLAS OWASP Top 10 for LLM Applications OWASP AIVSS OWASP Top 10 for Agentic Applications IBM AI Risk Atlas Cisco AI Security & Safety Framework CSA AI Controls Matrix Regional U.S. AI legislation, including NYC Local Law 144, California’s Transparency in Frontier AI Act, and Colorado AI Act Sector-specific AI legislation OECD AI Principles	AICPA SOC 2 (joint offering SOC 2 + AIUC-1) EU GDPR Canada Artificial Intelligence and Data Act (AIDA) ISO 27001

Combined AIUC-1 offerings

Framework	Joint offering details
SOC 2 + AIUC-1	AIUC and AICPA have partnered to offer SOC 2 + AIUC-1 together. Organizations earn a full SOC 2 attestation and AIUC-1 certification together in one engagement with the existing SOC 2 auditor. SOC 2 and AIUC-1 certification can be delivered by the same auditor in 6–10 weeks, resulting in one comprehensive audit report answering board and enterprise security questions in the age of AI.

AIUC-1 operationalizes emerging AI legislation and best practices

Framework	Description	How AIUC-1 compares
SOC 2	SOC 2 is the AICPA’s security attestation framework used by organizations to demonstrate controls over access, system operations, change management and vendor risk.	AIUC-1 complements SOC 2. Certification against AIUC-1: Addresses AI-specific controls not covered by SOC 2 Maps SOC 2’s TSCs to AI-specific requirements Includes quarterly third-party technical testing of agents against real-world risks SOC 2 crosswalk by criteria ->
EU AI Act	EU regulation classifying AI systems by risk levels (minimal, limited, high, unacceptable) with corresponding obligations	Operationalizes the EU AI Act by aligning with its requirements. Certification against AIUC-1 is a strong step towards compliance with the EU AI Act as it: Enables alignment towards minimal and limited risk systems Enables alignment towards high risk systems only if specific control activities are met (AIUC can help guide AI companies through this process) Provides documentation for internal conformity assessments for high risk systems as required in Annex VI EU AI Act crosswalk by article ->
NIST AI RMF	US government framework for managing AI risks throughout the AI lifecycle with four core functions: Govern, Map, Measure, Manage	Operationalizes the NIST AI RMF. Certification against AIUC-1: Translates NIST’s high-level actions into specific, auditable controls Provides concrete implementation guidance for key areas such as harmful output prevention, third-party testing and risk management practices NIST AI RMF crosswalk by function ->
ISO 42001	International standard for AI management systems (AIMS) covering responsible AI development and deployment	Aligns with ISO 42001. Certification against AIUC-1: Incorporates the majority of controls from ISO 42001 Translates ISO’s management system approach into concrete, auditable requirements Extends ISO 42001 with third-party testing requirements of, e.g., hallucinations and jailbreak attempts Addresses additional key concerns such as AI failure plans and AI-specific system security ISO 42001 crosswalk by clause ->
MITRE ATLAS	Knowledge base of adversarial tactics, techniques and mitigation strategies for machine learning systems, similar to MITRE ATT&CK for cybersecurity	Integrates MITRE ATLAS, which is a technical contributor to AIUC-1. Certification against AIUC-1: Incorporates ATLAS mitigation strategies in requirements and controls Strengthens robustness against the adversarial tactics and techniques identified in ATLAS Goes beyond ATLAS’s focus on security alone MITRE ATLAS crosswalk by mitigation strategy ->
OWASP Top 10 for LLM Applications	Curated list of the most critical security threats to LLM and generative AI systems	Integrates OWASP’s Top 10 for LLM Applications. Certification against AIUC-1: Addresses Top 10 threats in requirements and controls Strengthens robustness against the threats identified with concrete requirements and controls Goes beyond OWASP’s focus on security alone OWASP Top 10 crosswalk by threat ->
OWASP AIVSS	Scoring system for quantifying how agentic capabilities amplify security risks, producing numerical scores (0-10) that combine technical vulnerability severity with agent-specific factors	Integrates the OWASP AIVSS, which is a technical contributor to AIUC-1. Certification against AIUC-1: Covers all agent risks identified in AIVSS Enables organizations to mitigate risks quantified in OWASP AIVSS Incorporates AIVSS agent risk amplification factors in standard requirements OWASP AIVSS crosswalk by risk ->
OWASP Top 10 for Agentic Applications	Curated list of the most critical security threats to autonomous AI agent systems	Integrates OWASP’s Top 10 for Agentic Applications. Certification against AIUC-1: Addresses Top 10 agentic threats in requirements and controls Strengthens robustness against the threats identified with concrete requirements and controls Goes beyond OWASP’s focus on agentic risk alone OWASP Top 10 for Agentic Applications crosswalk by threat ->
IBM AI Risk Atlas	Comprehensive taxonomy of risks associated with ML models, GenAI, and AI Agents from IBM Research	Integrates IBM Research’s AI Risk Atlas, where IBM Research is a technical contributor to AIUC-1. Certification against AIUC-1: Maps AI Risk Atlas risks to concrete requirements and controls Strengthens robustness against risks with concrete requirements and controls Goes beyond AI Risk Atlas’s risk identification alone IBM AI Risk Atlas crosswalk by risk ->
Cisco AI Security & Safety Framework	Comprehensive AI threat landscape taxonomy identifying 19 attacker objectives with 150+ subtechniques	Integrates Cisco’s AI Security Framework, where Cisco is a technical contributor to AIUC-1. Certification against AIUC-1: Maps Cisco’s AI threat taxonomy to concrete requirements and controls Strengthens robustness against the attacker objectives and subtechniques identified by Cisco Goes beyond threat identification to provide actionable, auditable requirements Cisco AI Security Framework crosswalk by threats ->
CSA AI Controls Matrix	Cloud Security Alliance’s AI Controls Matrix providing security controls framework specifically designed for AI/ML systems	Certification against AIUC-1: Addresses key controls for AI vendors from the AICM such as adversarial robustness, system transparency, and documentation of criteria for cloud and on-prem processing Enables a compliance burden significantly lower than CSA’s AICM due to its targeted focus on top AI enterprise concerns Avoids duplicating controls in areas where CSA is industry-leading, such as data center infrastructure, physical server security, and other domains outside of the AIUC-1 scope CSA AICM crosswalk by control ->
Regional U.S. regulation	e.g. NYC Local Law 144, California TFAIA, Colorado AI Act (SB 24-205)	Simplifies alignment with regional U.S. regulation. Certification against AIUC-1: Addresses top concerns of emerging regional U.S. regulations such as the Colorado AI Act (SB 24-205) and NYC Local Law 144 Integrates controls for compliance obligations such as human-in-the-loop, appropriate data handling, and labelling AI clearly Helps organizations proactively prepare for obligations from emerging AI legislation before entering into force NYC Local Law 144 crosswalk by section -> Colorado AI Act crosswalk by section -> California TFAIA crosswalk by section ->
Sector-specific regulation	e.g. HIPAA, Fair Credit Reporting Act, Fair Housing Act, FTC guidance on AI & algorithms	Simplifies alignment with AI requirements in sector-specific regulation. Certification against AIUC-1: Prepares organizations to comply with, e.g., FTC guidance on AI & algorithms Addresses top concerns in sector-specific regulations such as discrimination and bias, human-in-the-loop, monitoring and logging, third-party interactions, and data handling in base requirements Offers AI companies optional add-on requirements for relevant use cases, e.g., for financial transactions and PII handling
OECD AI Principles	First inter-governmental AI standard (2019, updated 2024) with five principles for trustworthy AI adopted by 47+ countries	Operationalizes OECD’s AI Principles. Certification against AIUC-1: Translates OECD’s five principles into concrete, auditable requirements Addresses additional key areas such as third-party testing, AI failure plans, and adversarial resilience

Frameworks outside the scope of AIUC-1

Framework	Description	How AIUC-1 compares
Additional ISO standards including ISO 27001 and ISO 42006	International standards for, e.g., information security management systems (ISMS)	Certification against AIUC-1: Focuses on ISO 42001, which is specific to AI systems Extends several ISO 27001 controls into the AI domain including the Confidentiality-Integrity-Availability triad AIUC is following the newly-introduced ISO 42006 standard closely.
EU GDPR	European data protection regulation with AI-relevant provisions on automated decision-making, profiling, and data subject rights	AIUC-1 does not duplicate GDPR.
Canada Artificial Intelligence and Data Act (AIDA)	Canada’s proposed Artificial Intelligence and Data Act regulating AI systems based on impact assessments and risk mitigation	AIDA has not been passed into law yet. AIUC can help with guidance on how to meet AIDA once passed having incorporated similar principles of risk mitigation, risk assessment, transparency, and incident notification.

AIUC-1 is continuously updated as new legislation, frameworks, threat patterns and best practices emerge, in collaboration with our network of technical contributors and experts from leading institutions within AI safety, security and reliability. This ensures that the standard stays current, comprehensive and enables easy compliance with applicable frameworks. Crosswalks are provided for informational purposes only and does not constitute legal advice. Last updated October 15, 2026.

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AIUC-1 operationalizes emerging AI frameworks

AIUC-1 operationalizes emerging AI frameworks

Combined AIUC-1 offerings

AIUC-1 operationalizes emerging AI legislation and best practices

Frameworks outside the scope of AIUC-1

​AIUC-1 operationalizes emerging AI frameworks

​Combined AIUC-1 offerings

​AIUC-1 operationalizes emerging AI legislation and best practices

​Frameworks outside the scope of AIUC-1

AIUC-1 operationalizes emerging AI frameworks

Combined AIUC-1 offerings

AIUC-1 operationalizes emerging AI legislation and best practices

Frameworks outside the scope of AIUC-1