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         article-type="Research Paper"
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  <front>
    <journal-meta>
      <journal-title-group>
        <journal-title>Journal of Artificial Intelligence and Big Data Disciplines</journal-title>
        <abbrev-journal-title abbrev-type="publisher">jaibdd</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="epub">3049-2122</issn>
      <publisher>
        <publisher-name>Dr. Aaluri Seenu</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">jaibdd230073</article-id>
      <title-group>
        <article-title>Autonomous Compliance by Design: Agentic AI for Global Data Center Risk Governance</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Vinay</surname>
            <given-names>Dasari</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
      </contrib-group>
      <aff id="aff1">JNTU</aff>
      <pub-date pub-type="epub" iso-8601-date="2026-05-18">
        <month>05</month>
        <day>18</day>
        <year>2026</year>
      </pub-date>
      <volume>2</volume>
      <issue>2</issue>
      <abstract>
        <p>How can compliance ecosystems be designed as self-healing systems, resilient to breaches and capable of automatically preventing recurrences? Recent advances in agentic AI suggest technological solutions, even within current regulations. A case study in global risk governance for data centers demonstrates the research design, compliance ecosystem architecture, and three-dimensional self-healing anatomy: support, government, and control. Self-healing compliance ecosystems allow dynamic consumption of data in indicated modes and are self-healing in the enabling way of autonomic loops, embracing monitoring, remediation, and feedback. The design-supporting analysis suggests action-oriented responses to incidents, disaster recovery, and business continuity, while substantial performance improvements and lessons learned contribute to compliance resilience. Agentic AI allows an adaptive compliance ecosystem acting on behalf of a stakeholder body, enabling a self-healing compliance ecosystem.</p>
      </abstract>
      <kwd-group kwd-group-type="author">
        <kwd>Agent-based AI</kwd>
        <kwd>self-healing systems</kwd>
        <kwd>compliance</kwd>
        <kwd>governance</kwd>
        <kwd>resilience</kwd>
        <kwd>data centers</kwd>
        <kwd>risk management</kwd>
        <kwd>autonomic loops</kwd>
        <kwd>global issues</kwd>
        <kwd>ecosystems</kwd>
        <kwd>AI systems</kwd>
        <kwd>agentic AI</kwd>
        <kwd>privacy issues</kwd>
        <kwd>ethics</kwd>
        <kwd>trust</kwd>
        <kwd>auto-remediation</kwd>
        <kwd>monitoring</kwd>
        <kwd>social responsibility</kwd>
        <kwd>transparency</kwd>
        <kwd>societal needs</kwd>
        <kwd>safety</kwd>
        <kwd>artificial intelligences</kwd>
        <kwd>cybersecurity</kwd>
        <kwd>digital ecosystem</kwd>
        <kwd>technological development</kwd>
        <kwd>information technology</kwd>
        <kwd>cyberspace</kwd>
        <kwd>information and communications</kwd>
        <kwd>risk</kwd>
        <kwd>and compliance</kwd>
        <kwd>information systems</kwd>
        <kwd>use of agentic AI</kwd>
        <kwd>storage data center.</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
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</article>
