{"id":10524,"date":"2026-09-28T08:00:00","date_gmt":"2026-09-28T13:00:00","guid":{"rendered":"https:\/\/www.everylearnereverywhere.org\/?p=10524"},"modified":"2026-09-29T08:05:48","modified_gmt":"2026-09-29T13:05:48","slug":"ai-leadership-in-higher-education-starts-with-a-more-coherent-student-experience","status":"publish","type":"post","link":"https:\/\/www.everylearnereverywhere.org\/es\/blog\/ai-leadership-in-higher-education-starts-with-a-more-coherent-student-experience\/","title":{"rendered":"AI Leadership in Higher Education Starts With a More Coherent Student Experience"},"content":{"rendered":"

One way of understanding the last several years of work on digital teaching and learning is as a transition from fragmented to coherent. University departments, institution-wide project teams, and sector-wide collaborations have been building up capacity to ensure evidence-based teaching practices are enabled by technology in ways that benefit every learner. This transition from fragmented to coherent has been necessary to bring together the learnings from scattered implementation, promising experiments, limited pilot programs, unsynthesized data, and uneven access.<\/p>\n

Today, the fragmented experience students have had with digital learning more broadly is being echoed by the way AI in particular is influencing higher education. For example, in Student Research Into How Students and Faculty Use AI: Insights for Teaching and Learning<\/a>, which was developed by a group of Every Learner Everywhere student interns, one prominent finding is how conscious students are that their experience with AI varies greatly. They see how much it depends on individual faculty, what their major is, or their own personal financial resources or educational background. They are not experiencing a college education that responds to the AI transformation in a coherent way.<\/p>\n

The higher education sector could wait 20 years for that arc from fragmented to coherent to resolve itself, but that is much more dangerous with AI than it was with adaptive courseware or other previous digital learning technologies. AI is moving quickly from tool to infrastructure, and it is already influencing course design, student support, assessment, and institutional operations. Most critically, AI is restructuring how knowledge is produced, demonstrated, assessed, and valued.<\/p>\n

AI adoption has also outpaced any realistic expectation of banning it from the educational experience. Every month brings a fresh survey<\/a> of a growing percentage of students, faculty, and staff all using AI in their daily work, regardless of any policy to limit it. Every Learner\u2019s position on AI<\/a> is fundamentally the same as it always has been for digital learning \u2014 that it has tremendous potential to help close achievement gaps and improve learning for all students, but that this potential will not be realized automatically. It requires pairing thoughtful deployments of technology in support of evidence-based teaching practices. Every Learner is working with partners and institutions that take an AI posture of \u201cexplore, not ignore,\u201d and we particularly emphasize doing so in ways that are anchored in accessibility and evidence.<\/p>\n

The flood of surveys also show that the workplaces students will graduate into increasingly have AI use as part of everyday knowledge work. For example, a National Association of Colleges and Employers 2026 survey of employers<\/a> shows that the share of entry-level jobs requiring AI skills leapt from 13 to 35 percent in one year. A survey by Strada Education Foundation<\/a> shows that AI is decreasing the time employees in entry-level roles spend on \u201croutine\u201d tasks and increasing the time they spend on \u201canalytical and judgment-based responsibilities.\u201d Many colleges and universities, as a result, are considering AI literacies as a core graduation outcome, which in turn creates a fundamental capacity-building need for faculty that one-off workshops will not move.<\/p>\n

For all the reasons above, Every Learner believes AI presents higher education with a defining leadership moment. The future legitimacy of colleges and universities rests on getting the AI transition right for all students, not just those who happen to take courses that are part of pilot programs or taught by individual faculty who are AI curious. This moment will impact every student, so this moment asks higher education leaders to make values-based decisions at the same time they make technical decisions.<\/p>\n

Put another way, the AI transformation does not simply create the need to select, license, and deploy particular tools. Whether conscious of it or not, colleges and universities are engaged in a project that goes to the core of their mission, strategy, and governance. This moment calls for coherent, coordinated leadership.<\/p>\n

Moving from fragmented to coordinated AI adoption<\/h2>\n

You can observe fragmentation in the AI student experience in several ways:<\/p>\n