OIT AI-Automation Working Group

The Office of Information Technologies (OIT) has formed a working group to explore generative AI and the opportunities to improve operational efficiencies and automate routine operational tasks.


  • Project Prioritization and Roadmap: Develop a prioritized list of potential AI/Automation projects, along with a timeline and estimated costs for implementation.

  • Measurement and Evaluation: Identify metrics and KPIs for evaluating the success of the AI/Automation implementation.

  • Legal Aspects: Identification and reporting of risks is in scope, but rewriting policies is out of scope for this working group and will be evaluated at the university level.

Usage Focus

  • Assessment of Current State: An analysis of the current state in terms of AI/Automation maturity, including an inventory of any existing uses, capabilities, resources, skills, and technologies.

  • Market Analysis: A study of AI/Automation tools and trends in the industry.

  • Risk Management: Identify potential risks and challenges associated with AI/Automation tools, including technical, operational, and cultural risks, and strategies for mitigation.

  • Education, Governance, and Policy: Determine the user education and policies that should govern the use of AI/Automation tools within IT.

Innovation Focus

  • Identification of AI/Automation Opportunities: Identify specific areas where AI/Automation can add value. (Collecting ideas)

  • Technical Requirements: Specifications of the AI/Automation technologies, infrastructure, and data resources needed.

  • Skill and Talent Management: A plan for attracting, developing, and retaining AI/Automation talent, which could include internal training, recruiting strategies, or partnerships with external organizations.

  • Proof of Concept: Identify and perform proof of concepts (test beds) to validate assumptions and to gain additional insight into potential opportunities

  • Data: Determine the tools and techniques necessary to prepare data for use in AI/Automation use cases


The working group will prepare an initial report to the IT leadership by Spring 2024.


  1. John Buysse
  2. Tony Rimovsky 
  3. Brandon Rich
  4.  Justin Howell
  5. Kael Kanczuzewski
  6. Kaitlyn Barbour
  7. Kendall Smith
  8. Caela Kleber
  9. Jasmine DeWitt
  10. Chris Gillis
  11. Emily Scott
  12. Jaime Preciado- Beas
  13. Jim Baad