<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD with MathML3 v1.3 20210610//EN" "JATS-archivearticle1-3-mathml3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"
  dtd-version="1.3" xml:lang="en" article-type="research-article">
  <?DTDIdentifier.IdentifierValue -//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN?>
  <?DTDIdentifier.IdentifierType public?>
  <?SourceDTD.DTDName JATS-journalpublishing1.dtd?>
  <?SourceDTD.Version 1.2?>
  <?ConverterInfo.XSLTName jats2jats3.xsl?>
  <?ConverterInfo.Version 1?>
  <?properties open_access?>
  <front>
    <journal-meta>
      <journal-id journal-id-type="iso-abbrev">Arch Pharm Pract</journal-id>
      <journal-id journal-id-type="publisher-id">archivepp.com</journal-id>
      <journal-id journal-id-type="publisher-id">Arch Pharm Pract</journal-id>
      <journal-title-group>
        <journal-title>Archives of Pharmacy Practice</journal-title>
      </journal-title-group>
      <issn pub-type="epub">2320-5210</issn>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">archivepp.com-1262</article-id>
      <article-id pub-id-type="doi">10.51847/CFWu1QML8w</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Original research</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>A Practice Maturity Model for Moving from Digital Tools to Intelligence-Augmented Pharmacy</article-title>
      </title-group>
                    <contrib-group>
                      <contrib contrib-type="author">
              <name>
                <surname>Mendoza</surname>
                <given-names>Rafael</given-names>
              </name>
                              <xref rid="aff1" ref-type="aff">1</xref>
                                                            <xref rid="cor1" ref-type="corresp" />
                          </contrib>
                      <contrib contrib-type="author">
              <name>
                <surname>Cruz</surname>
                <given-names>Isabela</given-names>
              </name>
                              <xref rid="aff1" ref-type="aff">1</xref>
                                        </contrib>
                      <contrib contrib-type="author">
              <name>
                <surname>Lopez</surname>
                <given-names>Carlos</given-names>
              </name>
                              <xref rid="aff2" ref-type="aff">2</xref>
                                        </contrib>
                  </contrib-group>
                  <aff id="aff1">
            <label>1</label>Department of Pharmacy Practice Maturity and Digital Transformation, Faculty of Pharmacy, National Autonomous University of Mexico, Mexico City, Mexico.
          </aff>
                  <aff id="aff2">
            <label>2</label>Department of Intelligence-Augmented Pharmacy Services, Faculty of Pharmacy, Monterrey Institute of Technology, Monterrey, Mexico.
          </aff>
                          <author-notes>
            <corresp id="cor1">
              <bold>Address for correspondence:</bold> Prof. Wael Abu Dayyih, Department of
              Pharmaceutical Chemistry, Faculty of Pharmacy, Mutah University, Al-Karak 61710, Jordan.
                              E-mail: <email xlink:href="afael.mendoza@unam.mx">afael.mendoza@unam.mx</email>
                          </corresp>
          </author-notes>
                    <pub-date pub-type="epub">
        <day>30</day>
        <month>09</month>
        <year>2025</year>
      </pub-date>
      <volume>16</volume>
      <issue>3</issue>
      <fpage>79</fpage>
      <lpage>85</lpage>
      <permissions>
        <copyright-statement>
          Copyright: &#x000a9; 2026 Archives of Pharmacy Practice
        </copyright-statement>
        <copyright-year>2026</copyright-year>
        <license>
          <ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/"
            specific-use="textmining" content-type="ccbyncsalicense">
            https://creativecommons.org/licenses/by-nc-sa/4.0/</ali:license_ref>
          <license-p>This is an open access journal, and articles are distributed under the terms of
            the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows
            others to remix, tweak, and build upon the work non-commercially, as long as appropriate
            credit is given and the new creations are licensed under the identical terms.</license-p>
        </license>
      </permissions>
      <abstract>
        <title>A<sc>BSTRACT</sc></title>
        <p>Digital adoption in pharmacy is frequently inferred from the presence of electronic records, automated dispensing, decision-support alerts, or artificial-intelligence applications. Such indicators describe technological availability but do not establish whether an organization can use intelligence-generating systems safely, effectively, equitably, and accountably. This article proposes an original practice-maturity model for distinguishing digitization from governed intelligence augmentation. Organizational maturity is defined as the sustainable capability to align a bounded medication-use purpose with dependable data, task-appropriate evidence, workflow integration, professional authority, medication-safety controls, equity assessment, governance, workforce competence, and lifecycle learning. The model combines eight maturity domains, five organizational levels, and conjunctive transition gates. The levels progress from Digitized Foundation through Connected Rule-Based Support, Bounded Validated Intelligence, Supervised Workflow Augmentation, and Governed Intelligence Augmentation. Progression is non-compensatory: technical sophistication cannot offset a critical deficiency in data integrity, safety, human authority, equity, or accountability. Each transition therefore requires evidence appropriate to its claim, moving from infrastructure integrity to model assurance, prospective workflow evaluation, demonstrated practice value, and continuing lifecycle oversight. The model is intended for structured organizational self-assessment, comparative research, implementation planning, and identification of evidence gaps rather than numerical ranking or procurement approval. Validation should examine content validity, inter-rater reliability, construct validity, predictive validity, sensitivity to organizational change, and associations with workflow, safety, equity, and implementation outcomes. The framework remains conceptual, context-dependent, and reversible. It does not establish clinical benefit, regulatory conformity, universal applicability, or deployment readiness, but offers a testable architecture for evaluating when digital pharmacy becomes responsibly intelligence-augmented practice.</p>
      </abstract>
      <kwd-group>
                <kwd>Digital pharmacy</kwd>
                <kwd>Artificial intelligence</kwd>
                <kwd>Pharmacy practice</kwd>
                <kwd>Medication safety</kwd>
                <kwd>Human–AI collaboration</kwd>
                <kwd>Clinical decision support</kwd>
              </kwd-group>
    </article-meta>
  </front>
</article>