By Gerald R. Ford, CSCL (CSCMP), CPSM (ISM), CMC, SCMP (IFPSM); CEO, QCsolver Inc.; Analytics & Strategic Advisor, Kinetic GPO
Canadian colleges and universities are facing a familiar challenge: increasing demands on staff and faculty at a time when resources are under pressure. Artificial intelligence (AI) offers an opportunity to ease some of that burden, but its value depends less on having the newest technology than on knowing how to apply it effectively.
In my own work, I have used AI to tackle a range of projects from developing a 23-page business case to creating visuals, sorting supplier information from spreadsheets, and compiling summaries of regulatory requirements. These experiences reinforced an important lesson. AI is most useful when you provide clear direction and remain responsible for the final result.
Look for the workload bottlenecks
Higher education institutions generate enormous amounts of information. Procurement teams manage RFPs and contracts. Finance departments work with policies and reports. And administrative offices prepare briefing materials, correspondence, and presentations.
These are good places to explore AI because many involve repetitive or information-intensive work.
Consider a procurement department reviewing responses to an RFP. Rather than having staff manually sort every vendor question or organize common themes, AI can help categorize inquiries and produce an initial summary. Staff can then spend their time evaluating the issues and ensuring responses are accurate and consistent.
The key question is not simply, “Where can we use AI?” A better starting point is, “Which processes are taking our people too much time?”
Give AI enough direction
AI tools can produce impressive results, but they cannot read your mind. The quality of the output is heavily influenced by the quality of the instructions.
A useful prompt should establish the purpose of the task, who will use the resulting material, what form it should take, and any limitations that apply. For example, asking an AI tool to “summarize this procurement policy” leaves plenty of room for interpretation. Asking it to create a two-page plain language summary for university procurement staff, highlighting changes, responsibilities, and potential implementation issues, provides a much clearer target.
This approach is particularly valuable in higher education, where the same information may need to be presented differently to executives, faculty, students, suppliers, or administrative staff.
Start small and measure the results
Institutions do not need to launch an enterprise-wide AI initiative on day one. A focused pilot can provide much more useful insight.
A college might test AI to organize supplier documentation, create first drafts of internal briefing materials, or summarize lengthy policy documents. Procurement teams could experiment with tools that help categorize vendor information or identify recurring questions during competitive processes.
The objective should be measurable. How much staff time did the process previously require? How long does it take with AI assistance? Has consistency improved? Are there new review requirements?
Those answers can help determine whether a particular application is worth expanding.
Think beyond individual departments
AI can become more valuable when combined with collaborative approaches to procurement.
Higher education institutions participating in group purchasing organizations (GPOs), such as Kinetic GPO, already benefit from shared contracts, supplier relationships, and collective purchasing activity. AI can complement those models by helping staff organize supplier information, review documentation, and extract relevant information from agreements.
The technology does not replace procurement expertise. Instead, it can make existing information easier to work with and potentially reduce the administrative effort required to manage it.
Human judgment still matters
The temptation with AI is to focus on speed. But in higher education, accuracy, confidentiality, and accountability are equally important.
AI-generated material should be treated as a starting point, not an authoritative answer. Staff need to check facts, verify sources, review calculations, and ensure that recommendations align with institutional policies and applicable requirements.
Institutions should also establish clear expectations around confidential information, personal data, and proprietary documents before employees begin using AI tools for their work.
Build capability through experience
For higher education leaders, the goal should not be to find every possible application for AI. It should be to identify where the technology can make a meaningful difference without compromising quality or trust.
Used thoughtfully, AI can become more than another technology initiative. It can help colleges and universities reduce administrative friction, make better use of institutional knowledge, and give employees more time to focus on work that requires expertise, judgment, and human interaction.
