Pillar 3: Data Governance and Privacy Maturity Assessment

This maturity assessment tool is designed to help educational institutions evaluate their current state of AI governance in terms of data governance and privacy practices. The assessment covers the key components of Pillar 3 of the SAGE-AI Framework.

Who Should Participate?

This assessment should be completed by a cross-functional team including:

  • Senior leadership (e.g., President, Provost, CIO)
  • Data governance officers or committee members
  • AI/IT leadership
  • Representatives from academic affairs and student services
  • Legal counsel
  • Privacy officers

How to Use This Assessment

Read each question carefully and select the answer that best describes your institution's current state. Be honest in your responses to get an accurate picture of your institution's maturity level. After completing the assessment, use the scoring guide to calculate your overall maturity level for Pillar 3. If you are completing multiple pillar assessments, transfer your score into the master score sheet.

Assessment Questions

  1. Do you have a comprehensive Data Governance Policy in place? (No, Partially Implemented, Fully Implemented)
  2. Have you established Data Stewardship roles and responsibilities? (No, Partially Implemented, Fully Implemented)
  3. Is there a Data Quality Management Process implemented? (No, Partially Implemented, Fully Implemented)
  4. Have you conducted a Data Privacy Impact Assessment for AI initiatives? (No, Partially Implemented, Fully Implemented)
  5. Is there a Data Security Framework tailored for AI applications? (No, Partially Implemented, Fully Implemented)
  6. Have you implemented data anonymization and de-identification techniques where necessary? (No, Partially Implemented, Fully Implemented)
  7. Is there ongoing Data Governance Training for staff and faculty? (No, Partially Implemented, Fully Implemented)
  8. Do you have mechanisms in place for data access control and monitoring? (No, Partially Implemented, Fully Implemented)

Scoring

For each question:

  • No = 0 points
  • Partially Implemented = 1 point
  • Fully Implemented = 2 points

Interpretation of Results

Based on your total score, your institution's maturity level can be categorized as follows:

  • Nascent Stage (0-4 points): Your institution is in the very early stages of developing data governance and privacy practices for AI. There may be some awareness, but formal policies and processes are largely absent. Focus on establishing a comprehensive Data Governance Policy and defining data stewardship roles.
  • Emerging Stage (5-9 points): Your institution has begun to implement data governance and privacy practices but the approach is still developing. Some key components like data quality management or privacy impact assessments may be in place but not fully developed or consistently applied. Work on formalizing processes, enhancing data security measures, and providing ongoing training.
  • Established Stage (10-15 points): Your institution has a clear and consistent approach to data governance and privacy in AI initiatives. Most key components are in place and functioning effectively. Focus on refining these processes, ensuring full integration across the institution, and adapting them to address emerging data challenges.
  • Transformative Stage (16-18 points): Your institution is at the forefront of data governance and privacy in AI. Comprehensive practices are fully integrated into all AI-related processes, driving responsible and secure AI innovation across the institution. Continue to refine and evolve your approach, potentially serving as a model for other institutions. Focus on advanced data governance strategies and contributing to the broader discourse on data privacy in AI.

Next Steps

Based on your assessment results:

  • Identify the areas where your institution scored lowest and prioritize these for improvement.
  • Develop action plans to address gaps in your data governance and privacy practices.
  • Set goals to progress to the next maturity stage, focusing on the key components that will help you advance.
  • Regularly reassess your maturity level to track progress and identify new areas for improvement.
  • Share best practices and lessons learned within your institution to foster a culture of strong data governance and privacy.
  • Consider assessing other pillars of the SAGE-AI Framework to get a comprehensive view of your institution's AI governance maturity.
  • For institutions at the Transformative stage, explore opportunities to contribute to the broader education community's understanding of data governance and privacy in AI.
Maturity Assessments