The Road to Global Alignment: Mapping AISA to NIST, ISO, and AEGIS
Why Alignment Matters in AI Security
AI has no borders, but regulations do. Every region and industry is racing to define how AI should be governed, secured, and trusted. The result is a maze of overlapping frameworks — from NIST’s AI Risk Management Framework in the United States, to ISO’s international standards, to Forrester’s AEGIS model, to the EU AI Act.
Each brings valuable guidance, but none alone can solve the full problem. Organizations building and deploying AI systems operate across multiple frameworks, each with different terminology, priorities, and levels of enforcement.
That’s where the AI Security Alliance (AISA) steps in. AISA’s mission is to create the connective tissue that unites these global efforts into one operational standard for AI security, governance, and risk management.
The Challenge: Fragmentation in AI Standards
AI risk doesn’t fit neatly into existing compliance categories.
Traditional frameworks were built for data protection or software assurance — not for adaptive systems that learn, infer, and evolve. Without a shared foundation, organizations are left interpreting how to prove “AI compliance” in isolation.
This fragmentation creates four key challenges:
Inconsistent definitions of AI risk. Every framework uses its own language and metrics.
Gaps between governance and security. Policy frameworks often stop short of prescribing actionable controls.
Duplicated effort. Global companies must satisfy overlapping requirements with no clear mapping between them.
Slowed innovation. Without clarity, enterprises hesitate to deploy AI in regulated environments.
AISA is designed to bridge these divides — translating, aligning, and extending existing frameworks into a coherent, actionable model.
Mapping the Frameworks: How They Connect
AISA builds alignment across leading global standards. Each framework plays a vital role, but together they leave space for something new: a unifying operational layer.
NIST AI Risk Management Framework (AI RMF)
The NIST AI RMF defines four core functions: Map, Measure, Manage, and Govern.
It provides a structured way to assess and mitigate AI risk across development and deployment. However, NIST is intentionally flexible — it offers principles, not prescriptive controls.
AISA builds on NIST by adding specificity: standardizing how to identify sensitive data in AI systems, monitor model exposure, and enforce security policies at scale.
ISO/IEC 42001
ISO’s first AI management system standard focuses on responsible development, transparency, and lifecycle management. It provides governance scaffolding but does not specify how to detect, protect, or respond to emerging AI risks.
AISA extends ISO’s approach with data-driven control: mapping ISO governance objectives to measurable AI security actions such as classification, access control, and retention policies.
Forrester’s AEGIS Framework
AEGIS (AI Governance, Ethics, and Security) defines a practical model for organizations to assess maturity and accountability. It combines governance and risk assessment with an emphasis on explainability and resilience.
AISA complements AEGIS with technical depth: linking governance outcomes to operational benchmarks for data protection, model monitoring, and risk scoring.
The EU AI Act
The EU AI Act is the most comprehensive legislative framework to date, classifying AI systems by risk level and setting compliance obligations. It sets global precedent for accountability but focuses on classification, not implementation.
AISA aligns with the EU AI Act’s tiers of risk by providing practical methods to identify, assess, and mitigate risk using measurable data and controls.
Other Emerging Frameworks
AISA also tracks and integrates insights from:
Singapore’s Model AI Governance Framework (human oversight and explainability)
OECD AI Principles (transparency, accountability, and human-centric values)
UK AI Assurance Roadmap (testing and verification approaches for AI systems)
Canadian AI and Data Act (AIDA) (risk-based accountability for AI use)
Each contributes to the global conversation. AISA’s value lies in harmonizing them into one consistent, interoperable model.
The AISA Alignment Model
AISA’s alignment framework bridges these standards through three layers:
Governance Alignment: Mapping organizational policies to shared global expectations.
Common taxonomy for AI risk classification
Mapped roles and responsibilities across frameworks
Global reporting alignment for compliance
Security and Control Alignment: Translating governance into enforceable technical standards.
Data discovery and classification for AI datasets
Access and privilege management for model and pipeline protection
Monitoring and alerting for anomalous activity or data drift
Operational Alignment: Defining how organizations apply, measure, and sustain compliance.
Continuous assessment against AI risk indicators
Centralized dashboards for AI risk posture
Cross-framework audit readiness and documentation
Through these layers, AISA provides a single operational reference for compliance teams, engineers, and regulators — one that aligns with global policy while enabling practical enforcement.
Why Alignment Accelerates Trust
Global alignment is not just about compliance; it is about credibility.
When organizations can show alignment to AISA’s framework — backed by mappings to NIST, ISO, and the EU AI Act — they demonstrate maturity, transparency, and control.
That visibility builds trust with customers, regulators, and the public. It transforms AI security from a patchwork of requirements into a measurable, consistent discipline.
The Path Forward
AISA’s goal is to unify the AI ecosystem under one shared framework for visibility, control, and compliance.
Through collaborative research, working groups, and technical mapping, AISA is building a Global Alignment Framework for AI Security that will evolve alongside regulation and technology.
The message is simple: AI security needs standards as universal as the systems it protects.
AISA is defining that standard.
Join the Effort
Global collaboration starts with alignment.
Join the AI Security Alliance to participate in working groups, contribute expertise, and help define the global framework that will shape the future of AI security and compliance.
Join AISA and help make secure, responsible AI the global standard.
