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April 29, 2026International Journal of Technology & Emerging Research0 citations

Enterprise Data Governance Plan for Artificial Intelligence Initiatives: A Framework for Innovate Software Consulting Inc Ltd

SKShivanand R Koppalkar

Key Points

  • The aim is to establish a comprehensive data governance framework to enhance AI project management at Innovate Software Consulting.
  • Developed an enterprise data governance plan encompassing seven governance areas.
  • Utilized two AI tools, Claude and Gemini, to simulate feedback from four C-suite leaders.
  • Adhered to the NIST AI Risk Management Framework and mapped to various legal regulations.
  • The governance plan identified key areas for improvement in data quality and ethical AI practices.
  • Feedback from C-suite leaders highlighted the importance of privacy and accountability in AI projects.
  • Compliance mapping indicated alignment with GDPR, CCPA, HIPAA, FCRA, and ECOA rules for ongoing monitoring.

Abstract

This paper presents an enterprise data governance plan for all artificial intelligence (AI) projects at Innovate Software Consulting Inc Ltd. The company offers Oracle Human Capital Management (HCM) Cloud services, business-to-business (B2B) credit risk tools, electronic Integrated Healthcare Management Systems (e-IHMS), and enterprise analytics solutions. The plan covers seven governance areas: data ownership, data quality, privacy and security, lifecycle management, accountability, ethical AI, and ongoing compliance monitoring. It builds on the AI vision statement, ethical AI framework, team structure proposal, and executive review exercise. Two AI tools, Claude (Anthropic) and Gemini (Google), simulate reviews from four C-suite leaders: Chief Legal Counsel, Chief Financial Officer, Chief Operating Officer, and Chief Executive Officer. A critical reflection ties together the feedback and identifies areas for improvement. The plan follows the NIST AI Risk Management Framework and maps to GDPR, CCPA, HIPAA, FCRA, and ECOA rules.

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Cite This Study

Shivanand R Koppalkar (2026) studied this question.

synapsesocial.com/papers/69f19f74edf4b468248064edhttps://doi.org/10.64823/ijter.2603004
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