Submit an idea

To get started, faculty and staff submit a project idea using the intake form. We review this information to understand your current workflows, evaluate feasibility, and determine if AI is the right tool to enhance your work.

Initial review

Once a semester, the AI team convenes to review proposal submissions, using an evaluation matrix. The team identifies potential candidates for AI intervention, based on technical feasibility, data readiness, potential impact, stakeholder bandwidth and ethical implications. Proposals that are not a good fit for AI will be directed to more relevant resources and teams.

Discovery call

Once proposals have been identified, the AI team meets with the requestor and their team to learn more about current processes and effort, data readiness and access, subject matter experts, available technical resources, and the broader goals and core problems to solve. 

Selection and triage

After collecting the necessary information, the AI team identifies the strongest proposals based on feasibility and impact, selecting as many as current bandwidth permits. Proposals requiring bespoke solutions (due to complexity, privacy needs, or scale) are designated as formal projects.

For other requests, the AI team provides consultation or training. The team selects as many items as current bandwidth permits; remaining viable proposals are placed in a queue for reconsideration during the next review cycle. Selected requestors are notified via email.

Team Assemble

The requestor assembles a team of subject matter experts and end users. The AI team assigns a tech lead and a set of Computer Science students to work on the project, based on skills and interests. If the project involves an organizational design component, OED (Organizational Design and Efficiency) assigns a consultant from their team. Weekly sprints meetings are scheduled.

Project kick-off!

The entire team, including stakeholders, tech lead, organizational consultant and students, meet to explore challenges and opportunities for AI intervention in their workflow and identify which key problem to focus on. The team then formalizes a clear sprint goal and creates an actionable plan.