EDUCAUSE QuickPoll Results: AI-Related Procurement

EDUCAUSE is helping institutional leaders, IT professionals, and other staff address their pressing challenges by sharing existing data and gathering new data from the higher education community. This report is based on an EDUCAUSE QuickPoll. QuickPolls enable us to rapidly gather, analyze, and share input from our community about specific emerging topics.^Footnote1

The Challenge

The authors of a recent article in EDUCAUSE Review interviewed 12 procurement-related professionals to provide AI-related procurement guidance to the higher education community.^Footnote2 This QuickPoll builds on that work, exploring how procurement processes account for AI tools, what challenges and opportunities procurement professionals are encountering, and what actions can be taken to improve AI-related procurement. For the purposes of this QuickPoll, we define AI procurement as "the processes and considerations involved in acquiring tools, systems, and services that incorporate AI. The scope of AI procurement includes purchasing new AI-enabled tools, screening existing software for added AI capabilities, partnering with AI companies to develop custom solutions using institutional data, engaging consultants and other third parties that may use AI during the engagement, and even developing proprietary AI models." We broadly define AI products as "tools, systems, and services that incorporate AI."

The Bottom Line

A majority of QuickPoll respondents (63%) reported that their procurement processes either already account for AI products or will in the future. The greatest challenges for AI-related procurement are the inability to keep up with the high rate of change of AI products (45%) and insufficient AI-related institutional governance (40%). In general, an opportunity exists to include more stakeholders in the process—for example, even though 86% of respondents said that AI products are being used for teaching and learning at their institution, only 58% of respondents said that teaching and learning professionals are included in AI-related procurement. There is also an opportunity for increased collaboration with solution providers, with 21% of respondents citing opaque contract terms as one of their biggest challenges. Ultimately, supporting AI-related procurement processes is the responsibility not only of procurement professionals but also of end users and corporate partners.

The Data: Current and Planned Processes

Many (but not all) institutions already account for AI in procurement processes or plan to. Just under half of the respondents (49%) reported that their institution's procurement processes account for AI products. An additional 10% of respondents reported that although their current procurement processes do not account for AI products, changes are planned to account for AI products. A mere 5% of respondents reported that their procurement processes do not account for AI products and that the institution has no plans to do so in the future. Open-ended responses indicate that a lack of policy and stakeholder buy-in could make AI-related procurement processes a non-starter:

"Our institution is writing policies on AI products, so procurement is waiting for the policy to be approved before proceeding."

"We have tried to explain to [procurement] the importance of AI in considering products, but we have not made much progress."

We asked whether AI products, subsequent to their initial procurement, are reviewed against AI-related procurement questions to account for new functions and other developments. Of those who have AI-related procurement processes in place, just over a third (36%) said yes (see figure 1). Given how rapidly AI technologies are currently evolving, these data point to an opportunity for developing ongoing review processes.

Data security and compliance are top of mind. The security of institutional data, compliance with laws and regulations that govern the use of data, and the use of institutional data to train AI models top the list of factors procurement professionals attend to during AI-related procurement processes (86%, 86%, and 77%, respectively; see figure 2). Notably, algorithmic bias was the item least selected by respondents (30%), possibly due to challenges such as opaque contract terms or lack of AI literacy (see Common Challenges below). Open-ended responses included comments that the accessibility of AI products is also evaluated in procurement processes. For faculty, staff, and students with disabilities, AI products are a potential benefit but can also impose new barriers. In open-ended comments, respondents indicated that "lack of accessibility compliance with new AI tools" is one of their biggest procurement challenges. Accessibility experts recommend thorough and ongoing evaluation of AI products, not only to comply with relevant laws and regulations but also to support an inclusive learning environment.

The institutional digital divide extends to procurement processes. In the 2025 EDUCAUSE AI Landscape Study, we reported that larger institutions appear to have more AI-related resources available than smaller institutions.^Footnote4 Data from this QuickPoll align with that finding. For example, 44% of respondents from larger institutions (i.e., 5,000 students or more) said that their procurement processes account for AI products, compared to just 27% of respondents from institutions with fewer than 5,000 students. Similarly, 46% of respondents from larger institutions said that procurement professionals at their institution intend to make AI-related changes to procurement processes, compared to 29% of those at smaller institutions. These differences in procurement practices might be related to differences in the use of AI products at larger and smaller institutions. For example, 98% of respondents from larger institutions indicated that AI products were already being used or would soon be used for teaching and learning at their institution, and 93% said AI products were already being used or would soon be used in IT. Just 79% of respondents from smaller institutions said that AI products were being used in these areas. Certainly, correlation is not causation. Whether less AI tool use necessitates less AI tool procurement or less AI procurement inhibits AI use is unknown. Either way, such differences are concerning because they could reinforce or even enlarge digital equity gaps for students.

The Data: Who's Impacted and Who's Involved

AI, AI everywhere. Reflecting other research, such as the 2025 EDUCAUSE AI landscape study, QuickPoll respondents indicated that every area of their institutions is already using AI products (see figure 3). For every area listed in this closed-ended survey item, just 8% or fewer respondents said the area is not using AI products and will not be doing so anytime soon.

Not everyone gets a seat at the table. QuickPoll respondents indicated that technology, along with cybersecurity and data privacy, are the two institutional units most commonly included in the procurement of AI products (94% and 85%, respectively) at their institution (see figure 4). Despite teaching and learning consistently being ranked as the area of the institution most impacted by AI, teaching and learning was ranked as a distant third in terms of involvement in AI procurement, coming in at just over half (58%) of respondents.^Footnote5 This underrepresentation of teaching and learning professionals was also raised as a point of frustration in the recent report 2025 EDUCAUSE Teaching and Learning Workforce in Higher Education.^Footnote6 In open-ended comments, respondents reported that accessibility offices and general counsel are also included in procurement processes. Taken together, these data indicate that although AI-related procurement has strong support from technology, cybersecurity, and data privacy experts, other impacted stakeholders could be better represented.

Common Challenges

QuickPoll respondents were asked to select the three biggest challenges for AI tool procurement at their institution. The high rate of change of AI products and insufficient AI-related institutional governance ranked as the top two challenges (45% and 40%, respectively, see figure 5), indicating an opportunity for institutional leaders to shore up governance practices and also provide staff with more resources to stay abreast of the rapidly changing AI landscape. The lowest-ranked challenge on the list was "inability to evaluate products' environmental impacts," selected by just 1% of respondents. Based on our recent QuickPoll on sustainability, this low ranking is likely due to environmental factors being a low priority in procurement processes.^Footnote7 Notably, none of the challenges were selected by a majority of respondents, suggesting that institutions are facing unique and varied sets of challenges.

These data also point to an opportunity for stronger collaboration and support from solution providers. Just under a third of respondents (32%) cited costs or lack of budget as one of their biggest challenges, and opaque contract terms from solutions providers was selected by 21% of respondents. As one respondent explained, "We're hopeful that the HECVAT v4 will address some of these issues…. However, vendors haven't started utilizing [it]."^Footnote8 These findings dovetail with those in our QuickPoll from December 2024 about partnerships with solution providers, which indicated that institutional representatives are looking for solution provider partnerships based on transparency, communication, and shared understanding of the mission of higher education.^Footnote9

Promising Practices

Respondents also selected the three most helpful assets for AI-related procurement at their institutions. General procurement processes and clear contract terms from solution providers ranked as the top two assets, selected by 33% and 24% of respondents, respectively (see figure 6).

Finally, respondents were asked what action(s) staff and faculty should take to improve AI-related procurement, providing a useful guide for individuals, institutions, and solution providers.

For Individuals

• Develop critical AI fluency.
• Stay informed about ongoing AI developments.
• Do not use a purchasing card to buy an AI tool without formal review.
• Navigate the hype—don't rush to try new tools without evaluating them.

For Institutions

• Establish governance structures related to AI (e.g., data governance).
• Establish an AI community of practice.
• Provide end users with a list of products that have already been reviewed (both approved and not approved).
• Engage faculty in procurement processes.
• Articulate measurable benefits of AI products.
• Hold solution providers accountable for legal and regulatory compliance, including accessibility.
• Streamline procurement processes.
• Train faculty, staff, and students on procurement processes.
• Set clear expectations about capabilities, costs, and support.
• Develop and share detailed guidelines for evaluating AI products.
• Help stakeholders (from leaders to end users) understand the value of AI products.
• Explore products that have already been approved before trying new ones.

For Solution Providers

• Provide a human point of contact for institutional representatives.
• Understand and adhere to institutions' compliance needs.
• Clearly disclose how institutional data are used.
• Ask institutional representatives about their needs, and integrate targeted solutions into future products.
• Simplify contracts so that procurement professionals can easily understand them.

EDUCAUSE Resources

For more AI-related information and resources, visit Artificial Intelligence in the EDUCAUSE library or join the AI Community Group on EDUCAUSE Connect.

Notes

1. QuickPolls are less formal than EDUCAUSE survey research. They gather data in a single day instead of over several weeks and allow timely reporting of current issues. This poll was conducted between May 12 and 14, 2025, consisted of 16 questions, and resulted in 270 responses. The poll was distributed to EDUCAUSE members via relevant EDUCAUSE Community Groups. We are not able to associate responses with specific institutions. Our sample represents a range of institution types and FTE sizes. Jump back to footnote 1 in the text.↩
2. Susan Grajek, Kathe Pelletier and Austin Freeman, "AI Procurement in Higher Education: Benefits and Risks of Emerging Tools," EDUCAUSE Review, March 11, 2025. Jump back to footnote 2 in the text.↩
3. Percentages have been rounded to the nearest whole number, occasionally resulting in sums just under or over 100%. Jump back to footnote 3 in the text.↩
4. Jenay Robert and Mark McCormack, 2025 EDUCAUSE AI Landscape Study: Into the Digital AI Divide, research report (Boulder, CO: EDUCAUSE, February 2025). Jump back to footnote 4 in the text.↩
5. Robert and McCormack, 2025 EDUCAUSE AI Landscape Study. Jump back to footnote 5 in the text.↩
6. Kristen Gay, 2025 EDUCAUSE Teaching and Learning Workforce in Higher Education, research report (Boulder, CO: EDUAUSE: April 2025). Jump back to footnote 6 in the text.↩
7. Kristen Gay, "EDUCAUSE QuickPoll Results: Sustainability in Higher Education," EDUCAUSE Review, February 24, 2025. Jump back to footnote 7 in the text.↩
8. The latest version of the EDUCAUSE Higher Education Community Vendor Assessment Toolkit includes a dedicated AI module. Jump back to footnote 8 in the text.↩
9. Jenay Robert and Mark McCormack, "EDUCAUSE QuickPoll Results: Solution Provider Partnerships," EDUCAUSE Review, December 9, 2024. Jump back to footnote 9 in the text.↩

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Jenay Robert is Senior Researcher at EDUCAUSE.