https://taxonomy.eticas.ai/risk/organisational-readiness
Maturity: emerging
The risk that an AI system fails to deliver value not because of model performance issues but because it does not fit the organisational, technical, or human context into which it is deployed. This includes insufficient organisational capacity to absorb the technology, workflow incompatibility, interoperability failures with existing systems, and lack of sustainable maintenance capability.
This category is emerging. Assessment methods are still being developed. Definitions and subcategories may evolve.
Also known as: Integration Readiness · Deployment Readiness · Sociotechnical Fit
System type: ADM and LLM systems
Lifecycle stages: Pre Processing, Post Processing
Status. Each mapping shows what it rests on. Reviewed means a reviewer has confirmed the mapping against the concept’s current definition and the framework edition the taxonomy currently references; when the only confirmation is that of the person who wrote the mapping, it reads Reviewed (author’s confirmation). Outdated means it was reviewed, but the concept’s definition has changed since, so the review has to be repeated. The other statuses mean that no review has been recorded yet. Inherited mappings have been in the taxonomy since before v5.7.0 and are unchanged. They carry no record of who made them or how, and some were checked by hand when the taxonomy first published its mappings. Agent-proposed mappings come from a review carried out by AI agents, which read the framework’s text and the concept’s definition and agreed on the relation; no person has confirmed them yet. Provisional mappings were made without access to the framework’s text. Unreviewed mappings are older mappings whose target or relation was revised in v5.7.0, and any other mapping without a review. Mappings to a superseded edition of a framework are not shown: where the provision continues, they are carried to the current edition. Mappings a review has changed or rejected are not shown.
| Framework | Reference | Status |
|---|---|---|
| EU AI Act (Regulation 2024/1689) | Article 26(2) — assignment of human oversight to persons with the necessary competence, training and authority | Agent-proposed |
| EU AI Act (Regulation 2024/1689) | Article 4 — AI literacy | Reviewed (author’s confirmation) |
| ISO/IEC 42001:2023 — AI Management System | A.4.6 Human resources | Agent-proposed |
| ISO/IEC 42001:2023 — AI Management System | A.4.4 Tooling resources | Agent-proposed |
| ISO/IEC 42001:2023 — AI Management System | A.3 Internal organization | Agent-proposed |
| AIUC-1 — AI Underwriting Company Standard | Assign accountability | Inherited |
| Council of Europe Framework Convention on AI (CETS No. 225) | Article 16 — Risk and impact management framework | Inherited |
| NIST AI Risk Management Framework (AI 100-1) | MAP function | Inherited |
| NIST AI Risk Management Framework (AI 100-1) | GOVERN 4: Organizational teams are committed to a culture that considers and communicates AI risk. | Agent-proposed |
| NIST AI Risk Management Framework (AI 100-1) | GOVERN 2: Accountability structures are in place so that the appropriate teams and individuals are empowered, responsible, and trained for mapping, measuring, and managing AI risks. | Agent-proposed |
| NIST AI Risk Management Framework (AI 100-1) | MAP 1.4: The business value or context of business use has been clearly defined or – in the case of assessing existing AI systems – re-evaluated. | Agent-proposed |
| OECD AI Principles | 2.4 Building human capacity and preparing for labour market transformation | Agent-proposed |