{
  "abstract": "This conceptual research paper proposes an AI-native operating model for transforming customer interactions into organizational intelligence and continuous product learning.\n\nThe paper introduces an Interaction-to-Outcome Loop that connects customer interaction, contextual data, AI-assisted interpretation, product decisions, workflow interventions, and outcome measurement. It examines how this model can support continuous product improvement across both business-to-business (B2B) and business-to-consumer (B2C) environments.\n\nThe paper also introduces AI as a Performance Operating System (AI-POS) as a conceptual framework for connecting organizational objectives, AI-assisted intelligence, workflow orchestration, performance measurement, and governance.\n\nAn illustrative Digital Witness use case demonstrates how authorized contextual information, telemetry, application activity, and support signals could be transformed into structured intelligence for enterprise troubleshooting and product improvement.\n\nThe paper develops conceptual propositions and a research agenda for future empirical validation. It is intended to contribute to discussions of AI-native product management, organizational learning, enterprise AI, and continuous product improvement.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "name": "Richard Barigela"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/crmzj1xmw93kh.bib",
  "cited_by": 0,
  "doi": "10.5281/zenodo.23619772",
  "fulltext_url": null,
  "id": "crmzj1xmw93kh",
  "issns": [],
  "landing_url": "https://zenodo.org/records/23619772",
  "language": "eng",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [],
  "openalex": null,
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-24",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/crmzj1xmw93kh.ris",
  "sources": [
    {
      "first_seen": "2026-11-07T12:20:44Z",
      "native_id": "23619772",
      "source": "zenodo",
      "url": "https://zenodo.org/records/23619772"
    }
  ],
  "subjects": [],
  "title": "From Customer Interaction to Organizational Intelligence: An AI-Native Operating Model for Continuous Product Learning",
  "title_text": "From Customer Interaction to Organizational Intelligence: An AI-Native Operating Model for Continuous Product Learning",
  "type": "preprint",
  "updated_at": "2026-11-07T12:20:44Z",
  "url": "https://research.draconitic.com/paper/crmzj1xmw93kh",
  "venue": "Zenodo",
  "versions": []
}