The growing role of machine learning and AI in higher education research is providing new challenges and opportunities for researchers and IT staff alike. With access to more and larger datasets for numerous disciplines, IT staff should expect to work with increasing numbers of researchers using machine learning in the coming years. It's important that IT groups begin planning how to help lower the barrier to entry at their institutions for researchers who hope to use machine learning in their labs and research projects. IT units can begin developing processes and conducting needs assessments now to determine their best course of action from a resource and benefits perspective.

Whatever their resources and plans for the future, a primary area of focus for both IT and researchers should be establishing clear processes and lines of communication to ensure both groups can align on their needs and goals. When communication happens early and often in these collaborative relationships, resources of both time and money can be saved on both sides. With IT involved in designing onboarding processes and documentation, IT units can be more successful in supporting, maintaining, and improving the machine learning experience for their end users.

The precise future of machine learning's use in higher education research is uncertain, but working to support the ingenuity of faculty and the growth of science and research is something every institution can strive for. Each step on the path toward developing better processes, communication, and support will help groups across institutions improve their understanding of how machine learning and AI may play a part in their future work. As long as there is a focus on being thoughtful and collaborative in the steps we take, and as long as we continue to evaluate our progress, we'll find the best way forward to support machine learning's growing role in research.