{
  "program": "WisdomTwin Research",
  "publisher": "WisdomTwin, Inc.",
  "brand": "WisdomTwin.ai",
  "landingUrl": "https://www.wisdomtwin.ai/research",
  "catalogUrl": "https://www.wisdomtwin.ai/research/catalog.json",
  "rssUrl": "https://www.wisdomtwin.ai/research/rss.xml",
  "updated": "2026-09-03",
  "papers": [
    {
      "id": "WT-100-001",
      "version": "2.0",
      "type": "Working paper / preprint",
      "peerReviewed": false,
      "title": "Judgment Latency in Regulated Enterprises: A Conceptual Framework and Research Agenda for Role-Specific AI Decision Support",
      "author": {
        "name": "Roman Bodnarchuk",
        "role": "Co-Founder and Chief Executive Officer",
        "affiliation": "WisdomTwin, Inc.",
        "location": "Toronto, Ontario, Canada",
        "email": "roman@wisdomtwin.ai",
        "orcid": "https://orcid.org/0009-0004-3113-2118"
      },
      "datePublished": "2026-09-03",
      "language": "en",
      "license": {
        "name": "Creative Commons Attribution 4.0 International (CC BY 4.0)",
        "url": "https://creativecommons.org/licenses/by/4.0/"
      },
      "doi": null,
      "doiStatus": "Pending repository deposit. No DOI has been issued.",
      "abstract": "Organizations can possess the information required for a decision while still waiting for a particular role to attend to it. This conceptual working paper defines judgment latency as the elapsed time between decision readiness and attention by the person or forum whose judgment is required. It proposes the AI Judgment Twin as a role-specific, evidence-grounded decision-support architecture, distinguishes the concept from personal simulation, and derives governance requirements for provenance, authorization, safe decline, human confirmation, monitoring, and contestability. The paper integrates research on work interruption, meetings, decision rights, organizational memory, digital and human twins, and human reliance on automation. It reproduces the assumptions behind McKinsey's 2019 estimate of about 530,000 manager-days and USD 250 million in annual wages, labels the \u201cabout one day per week\u201d restatement as author-derived arithmetic, introduces a non-overlapping model of potentially recovered time, and proposes six falsifiable propositions and a staged empirical evaluation protocol. The work reports no live-enterprise deployment or causal product-performance result.",
      "keywords": [
        "judgment latency",
        "AI-assisted decision making",
        "organizational memory",
        "decision rights",
        "regulated enterprises",
        "human oversight",
        "provenance",
        "asynchronous management",
        "model risk",
        "human-computer interaction"
      ],
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        "landingPage": "https://www.wisdomtwin.ai/research/wt-100-001",
        "pdf": "https://www.wisdomtwin.ai/research/papers/WT-100-001-v2.0.pdf",
        "markdownSourceRecord": "https://www.wisdomtwin.ai/research/wt-100-001.md",
        "bibtex": "https://www.wisdomtwin.ai/research/wt-100-001.bib",
        "ris": "https://www.wisdomtwin.ai/research/wt-100-001.ris"
      },
      "suggestedCitation": "Bodnarchuk, R. (2026). Judgment latency in regulated enterprises: A conceptual framework and research agenda for role-specific AI decision support (WisdomTwin Working Paper WT-100-001, Version 2.0). WisdomTwin, Inc.",
      "versionHistory": [
        {
          "version": "1.0",
          "date": "2026-09-03",
          "note": "Initial pre-publication draft; references flagged as unverified."
        },
        {
          "version": "2.0",
          "date": "2026-09-03",
          "note": "Fact-checked conceptual revision. Source caveats corrected, an unverifiable draft citation removed, McKinsey arithmetic reproduced and relabeled as author-derived, architecture claims converted to design requirements, propositions and evaluation protocol added, legal scope narrowed."
        }
      ],
      "disclosures": [
        "This is a conceptual working paper and preprint, not an empirical study and not peer reviewed.",
        "It reports no live-enterprise deployment or causal product-performance result.",
        "WisdomTwin is pre-revenue, has USD $0 product revenue, no production users, no paying customers, and five founder-built synthetic demonstrations.",
        "Roman Bodnarchuk is Co-Founder and CEO of WisdomTwin, Inc., is involved in developing the proposed architecture, and has a financial interest in its adoption.",
        "Generative AI assisted with source discovery, fact-checking, drafting, editing, and document production. The named author is responsible for the final text.",
        "No new empirical dataset was collected or analyzed.",
        "No external research funding was reported for preparation of the working paper."
      ],
      "notes": "The PDF is the version of record. This record contains no traction, customer, revenue, certification or validation claims."
    }
  ]
}