Realizing artificial intelligence (AI) can provide numerous benefits to organizations, such as creating efficiencies, many constituencies within the organization are vying for resources to develop and deploy AI projects. How do organizations make decisions regarding which projects get prioritized when the demand for support from data analytics teams surpasses the number of projects that can be worked on within a reasonable timeframe?

During this session, we will share our experiences using a systems-based approach to creating processes that address resource allocation for AI and other educational data projects within a college of health sciences owned by a large clinical delivery enterprise.

The first step in the systems-based approach involved gathering the appropriate stakeholders to create a process that would represent the varying needs of the college. This culminated in the creation of a Data Governance Committee. Knowing that the clinical system had access to resources that the college needed helped us implement step two, which entailed aligning and leveraging available resources to provide the momentum to move the process forward. Step three involved the review and approval of a pilot AI project for the MD Admissions process. Step four is moving to the next phase of implementing pieces of the MD AI project to other departments and divisions in the college that can benefit from the efficiencies the AI creates.