{
  "notice": "Illustrative mapping from the AI Governance Engineer Body of Knowledge v0.5.0 (not a claim of conformity)",
  "version": "0.5.0",
  "license": "CC BY 4.0",
  "licenseUrl": "https://creativecommons.org/licenses/by/4.0/",
  "schemaVersion": 1,
  "schema": "https://aigovernanceengineer.com/api/v1/schemas/control.json",
  "self": "https://aigovernanceengineer.com/api/v1/controls/aige-ctl-deploy-016.json",
  "source": "https://aigovernanceengineer.com/controls/deployment-and-monitoring#aige-ctl-deploy-016",
  "citation": {
    "title": "AI Governance Engineering: The Thesis & Body of Knowledge",
    "authors": [
      "Jorge García Aibar"
    ],
    "parentDoi": "https://doi.org/10.5281/zenodo.22956197",
    "conceptDoi": "https://doi.org/10.5281/zenodo.22857084"
  },
  "control": {
    "id": "AIGE-CTL-DEPLOY-016",
    "profile": "deployment-and-monitoring",
    "url": "https://aigovernanceengineer.com/controls/deployment-and-monitoring#aige-ctl-deploy-016",
    "json": "https://aigovernanceengineer.com/api/v1/controls/aige-ctl-deploy-016.json",
    "title": "People who work with agents trained, and the manual path kept",
    "version": "0.2",
    "status": "draft",
    "reviewerStatus": "open",
    "depth": "derived",
    "objective": "People who work with an agent every day are trained, on record, on its range of actions, its common failure modes, the usage policies for data and how to report an override or a wrong action, and each critical process the agent runs keeps a manual procedure and people who can still run it when the agent malfunctions or is unavailable.",
    "failureModes": [
      "People work with an agent they were never trained on, or no training record shows who was trained on what and when.",
      "The agent malfunctions or is unavailable and no one can still run a critical process it took over by hand.",
      "Users do not know how to report an override or a wrong action, so what they see never reaches the agent's owners."
    ],
    "scope": "AI agents that people use as part of their work, and the critical processes those agents run. The overseers who approve agent actions are covered by AIGE-CTL-DEPLOY-003.",
    "enforcementPoints": [
      "deploy",
      "periodic"
    ],
    "verification": [],
    "evidence": [
      {
        "artefact": "Training records per user and module; the manual procedure for each critical process the agent runs, with the people who can run it",
        "schemaId": "training-record",
        "schema": "https://aigovernanceengineer.com/schemas/training-record.v1.json",
        "layer": 4
      }
    ],
    "failureResponse": {
      "effect": "alert",
      "text": "A user with no current training record, or a critical process with no manual procedure or no one able to run it, is raised to the agent's owner."
    },
    "layer": 4,
    "secondaryLayers": [],
    "patterns": [],
    "seeds": [],
    "derivedFrom": [
      {
        "kind": "schema",
        "ref": "training-record",
        "url": "https://aigovernanceengineer.com/resources/templates#schema-training-record"
      },
      {
        "kind": "chapter",
        "ref": "governing-agents",
        "url": "https://aigovernanceengineer.com/bok/governing-agents"
      }
    ],
    "mappings": {
      "obligations": [
        {
          "id": "AIGE-OBL-EUAIA-ART4",
          "name": "EU AI Act Art. 4 AI literacy",
          "url": "https://aigovernanceengineer.com/obligations/aige-obl-euaia-art4"
        }
      ],
      "iso42001": [],
      "nistAiRmf": [
        {
          "id": "GOVERN 2.2",
          "title": "The organization’s personnel and partners receive AI risk management training to enable them to perform their duties and responsibilities consistent with related policies, procedures, and agreements."
        }
      ],
      "owasp": [],
      "atlas": [],
      "aiuc1": [],
      "csaAicm": [],
      "other": [
        {
          "framework": "IMDA MGF for Agentic AI v1.5",
          "ref": "2.4.3 Users who integrate agents into their work processes, p.47",
          "note": "Direct fit: Education on the agent's range of actions and failure modes, and training so users can still perform critical processes manually (also p.46)"
        }
      ]
    },
    "references": [
      {
        "n": 56,
        "title": "Governing AI agents",
        "text": "Governing AI agents (AI Governance Engineering Body of Knowledge v0.5.0, chapter 23, section \"Training users and keeping the manual path\"). AI Governance Engineer (Jorge García Aibar). 2026-09.",
        "url": "https://aigovernanceengineer.com/bok/governing-agents#training-users-and-keeping-the-manual-path",
        "verified": "primary"
      },
      {
        "n": 48,
        "title": "Governing deployment and use",
        "text": "Governing deployment and use (AI Governance Engineering Body of Knowledge v0.5.0, chapter 15, section \"Graduated degradation\"). AI Governance Engineer (Jorge García Aibar). 2026-09.",
        "url": "https://aigovernanceengineer.com/bok/governing-deployment#graduated-degradation",
        "verified": "primary"
      },
      {
        "n": 16,
        "title": "Regulation (EU) 2024/1689 (AI Act), consolidated text of 2026-07-27, Art. 4",
        "text": "Regulation (EU) 2024/1689 (AI Act), consolidated text of 2026-07-27, Art. 4 (providers and deployers take measures to support the AI literacy of their staff). Publications Office of the EU (EUR-Lex). 2026-07-27.",
        "url": "https://eur-lex.europa.eu/eli/reg/2024/1689/2026-07-27/eng#art_4",
        "verified": "primary"
      },
      {
        "n": 6,
        "title": "Artificial Intelligence Risk Management Framework (AI RMF 1.0), NIST AI 100-1",
        "text": "Artificial Intelligence Risk Management Framework (AI RMF 1.0), NIST AI 100-1 (subcategories cited by id: GOVERN 1.6, 1.7, 2.1, 2.2, 6.1; MAP 1.1, 3.5; MEASURE 2.3, 2.4, 2.11, 3.1, 3.3; MANAGE 1.1, 2.4, 3.1, 4.1, 4.3). NIST. 2023-01-26.",
        "url": "https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.100-1.pdf",
        "verified": "primary"
      },
      {
        "n": 7,
        "title": "Model AI Governance Framework for Agentic AI, v1.5",
        "text": "Model AI Governance Framework for Agentic AI, v1.5 (published 2026-05-20, updated 2026-06-05; four dimensions: assess and bound the risks upfront, make humans meaningfully accountable, implement technical controls and processes, enable end-user responsibility). IMDA. 2026-06-05.",
        "url": "https://www.imda.gov.sg/-/media/imda/files/about/emerging-tech-and-research/artificial-intelligence/mgf-for-agentic-ai.pdf",
        "verified": "primary"
      }
    ],
    "implementationNotes": [
      "The degraded modes of chapter 15 assume that a person can do the work: keep the manual procedure next to the agent's deactivation policy, and the people who can run it on the roster."
    ],
    "openQuestions": [
      "Verification procedure to be specified: the source material states what the control produces, not how a third party checks it; requires technical review.",
      "How often a manual procedure must be exercised to count as kept is left open: the source material asks that core skills be retained through training and work exposure, without a frequency."
    ],
    "observation": null,
    "observationSchema": "https://aigovernanceengineer.com/schemas/control-observation.v1.json",
    "examples": []
  }
}