Editorial library
Reference sources for the SME AI transition
Resources
Primary sources, practical references, and terminology for SMEs adopting AI while retaining human oversight.
The resource library supports decisions across the Framework: understanding capabilities, setting boundaries, evaluating pilots, and operating with monitoring and accountability.
External links favor public institutions, standards bodies, research organizations, and protocol maintainers. Inclusion is editorial, not an endorsement. The glossary provides concise internal definitions for terms used throughout the site.
Governance & policy
Reference material
Primary-source guidance and reports that help organizations build context before choosing tools, training, or implementation paths.
NIST AI Risk Management Framework
ExternalA practical framework for identifying, managing, and governing AI-related risks across the lifecycle.
NIST
NIST AI Resource Center
ExternalA central index of NIST AI guidance, standards activity, and supporting materials relevant to organizations adopting AI.
NIST AI Resource Center
OECD AI Policy Observatory
ExternalInternational policy, measurement, and governance resources covering national AI strategies and policy developments.
OECD.AI
EU AI Act Overview
ExternalEuropean Commission guidance and overview material on the EU regulatory framework for artificial intelligence.
European Commission
NIST Generative AI Profile
ExternalA companion profile applying the AI Risk Management Framework to risks that are distinctive to or intensified by generative AI.
NIST
Reports & benchmarks
Reference material
Primary-source guidance and reports that help organizations build context before choosing tools, training, or implementation paths.
Stanford AI Index Report 2026
ExternalThe current annual benchmark covering global AI research, technical performance, responsible AI, economics, policy, and adoption signals.
Stanford HAI
AI Adoption by Small and Medium-sized Enterprises
ExternalOECD analysis of SME adoption barriers, enabling conditions, policy responses, and recommendations.
OECD
Protocols & interoperability
Reference material
Primary-source guidance and reports that help organizations build context before choosing tools, training, or implementation paths.
Procurement & evaluation
Reference material
Primary-source guidance and reports that help organizations build context before choosing tools, training, or implementation paths.
Workforce & change
Reference material
Primary-source guidance and reports that help organizations build context before choosing tools, training, or implementation paths.
Glossary
Core terminology for AI adoption
AI Model
A trained computational system capable of generating outputs based on input data.
Agent
Software capable of performing tasks autonomously by interacting with tools or systems.
Agentic System
A system where AI performs multi-step workflows toward a defined objective.
Model Context Protocol (MCP)
A protocol allowing AI models to interact with tools, data sources, and services.
Human in the Loop
A workflow in which a person reviews, approves, corrects, or escalates an AI system's work.
Retrieval-Augmented Generation (RAG)
A pattern that supplies a model with retrieved information before it generates a response.
AI Governance
The roles, rules, controls, and review processes used to direct and oversee AI systems.
Model Evaluation
A structured test of whether an AI model or system meets defined quality, safety, cost, and operating requirements.
Prompt Injection
An attempt to make an AI system follow untrusted instructions that conflict with its intended rules.
Workflow Automation
The use of software to execute or coordinate repeatable steps in a business process.