Institutions are primarily accommodating AI-related work by upskilling existing staff. Asked about their AI-related work responsibilities, 61% of this year's respondents said they have work responsibilities related to AI, compared to 56% in 2024. In open-ended comments, respondents described AI-related tasks spanning every area of the institution, from teaching and learning and student services to daily operations. Indeed, "existing employee adoption of AI responsibilities" appears to be the approach many institutions are taking for staffing their AI-related needs. A mere 1% of respondents reported that their institution is supporting needed AI-related skills primarily by hiring new faculty or staff, whereas 37% of respondents reported that they are supporting these skills needs by upskilling or reskilling existing faculty or staff (see figure 23). Notably, more than a quarter of respondents (27%) indicated that their institutions are not increasing AI-related skills for their workforces.

In addition to upskilling and reskilling existing faculty or staff, some institutions are also creating new or restructuring existing non-leadership and leadership positions and doing so at a higher rate than in 2024 (see figure 24). Given how few respondents reported hiring new staff, we might speculate that existing faculty or staff are also moving into these restructured or newly created positions, potentially creating vacancies or reduced staff capacity in other functional areas of the institution in order to support emerging AI needs. This hypothesis is supported by respondents' open-ended comments. For example, one respondent reported, "The AVP for academic technology has been told to devote 80% of his workday to AI."

Finally, asked specifically about the AI-related skills needed among their faculty and staff, respondents highlighted "AI literacy" for both groups, as well as "boosting productivity" for staff and "best practices for teaching" for faculty (see figure 25). Interestingly, "data governance" and "cybersecurity" were reported as much more important skills for staff than for faculty, despite respondents' emphasis elsewhere on the benefits of AI for learning analytics and the critical role faculty will undoubtedly play in advancing that work for the institution.