By Ashish Fernando, CEO & Founder, EDMO
Higher education has never advanced alone. Every era of progress has been a function of partnership, with employers, with communities, with the technologies of the moment. What is different now is the nature of the partner. For the first time, institutions are being asked to collaborate not with a new tool, but with a new kind of capability: one that drafts, advises, analyzes, and improves with use.
The most significant development in the last year hasn’t been the fact that colleges are embracing AI since almost all of them have done so. Rather, it is the case that the most progressive institutions have moved away from seeing AI as just an experiment and now regard it as part of their infrastructure, making this change on purpose by means of work that is aligned with their mission rather than through one-size-fits-all implementations.
The different institutions involved in this change are not following the same strategy, and that is the most encouraging aspect. Miami Dade College, which has just introduced Florida’s first bachelor’s degree in applied AI, has recently obtained $2 million from Google.org to help expand a national consortium aimed at preparing students for careers that are driven by AI. Meanwhile, National University has developed a framework that it refers to as About, With, and Beyond AI in order to prepare students for both the technological and the human aspects of the work ahead.
AI should not be used in higher education as a substitute for humans; that way of putting it is both too restricted and too lacking in creativity. Instead, the possibility lies in having AI work alongside faculty members, advisors, admissions staff, and student support personnel so as to take on repetitive tasks, increase capacity, and enable the institutions to react at the speed that students currently expect. The evidence from these campuses all indicates the same thing: the benefits are not derived from automation for its own sake, but come from AI detecting when a student is falling behind and prompting a timely, human response.
That principle is gradually altering the way students enroll, since many universities are not ready for it. Instead of asking those initial questions during a visit to campus or by filling out an enquiry form, a prospective student is now more likely to ask them through an AI interface: Which course suits my background? What credits will transfer? What financial aid is available? If the response given is general, out of date or missing altogether, the institution may lose its relevance without even knowing that the student had existed. At the same time, admissions staff spend their days answering the same limited range of questions: current status, the required documents, deadlines, eligibility, and the next steps — questions which almost never require them to begin from scratch. AI can take care of that first stage of interaction continuously, across
different channels and languages, in a consistent manner. When managed properly, it does not replace the human relationship; rather, it preserves the time needed to build that relationship.
Yet having capability without discipline is a disadvantage, and the most effective institutions are honest about this point. Instead of pretending that AI can be got rid of altogether, Western Governors University drew a clear distinction between using AI as a tool for learning and using it to avoid learning and found that students appreciated the clarity. WGU also took further steps by helping to establish the Credential Integrity Action Alliance in order to defend the value of the degree itself, while other institutions are re-designing their methods of assessment to focus on an authentic display of ability: oral defenses, version tracking, and performance tasks which are hard to fake. This is what maturity entails—not enthusiasm, not fear—but governance that is introduced early on and in an open manner.
The institutions which will succeed won’t be those that spend the most on AI; instead, they will be the ones that establish the strongest AI partnerships.
These partnerships operate in two directions. The first involves institutions and the technology they take on. An AI system which has not been trained on the institution’s knowledge, is not aligned with the institution’s policies, and has not been incorporated into the current systems is not an asset; it is a liability even though it has a friendly interface. A chatbot that responds with confidence but is inaccurate is not an example of innovation. A document system that saves time but cannot be audited is not an advance. In the field of higher education, trust is not something that is added on later; it is the result.
The second collaboration exists between administrators and educators. AI should not be something imposed on faculty and staff; it must be developed together with them since they are the ones who know where difficulties actually occur, what questions are asked every day, which procedures fail during the busy period, in what situations judgment is necessary and in what cases automation is appropriate. The proper way to judge any tool is not by how fast it gives an answer, but by whether the student has come out of the experience in a better position- has their understanding been enhanced, or has the tool merely supplied the answer?
We have a duty, as leaders, to oppose both the view that AI will solve all our problems and the idea that it is too risky to engage with. Both of these positions are dishonest. Students, employers, and society have already taken steps in this direction. The only real issue now is whether we guide the development of AI deliberately or simply accept it without doing so.
The discipline needed isn’t complicated, even though it is demanding. Begin by focusing on the mission, identify the points at which students encounter difficulties and the places where staff waste hours on repetitive tasks, select the applications in which AI can increase speed, accuracy, access, or support and make sure people are kept informed in all cases where judgment is involved, keep track of what actually takes place, establish governance before it is actually required, and provide continuous training then make improvements based on that.
Even in higher education there is no need for AI if what is wanted is for it to become less human; instead, it needs AI so that its staff can spend more of their time on the more human aspects of their work, such as teaching, giving advice, providing mentorship, making decisions, and guiding students through the experiences that change their lives.
The next major partnership in higher education won’t be one between institutions and machines but will instead take place among institutions, educators, and the technology they select, collaborating to create a student experience which is faster, fairer, more personal and more scalable than the one that existed before.
That is the future we should build.
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