Beyond Tool or Threat: GenAI and the Challenge It Poses to Higher Education

Confidence in higher education is collapsing. In 2015, 57 percent of Americans told Gallup they had "a great deal" or "quite a lot" of trust in colleges and universities; today, that figure stands at 36 percent.^Footnote1 Fewer Americans view a college degree as very important for securing a well-paying job, and nearly half of employers plan to drop degree requirements for certain roles.

Technology, including generative artificial intelligence (GenAI), is just one force accelerating change in higher education, alongside economic, political, and cultural pressures that long predate ChatGPT. But GenAI is a more powerful catalyst, exposing the degree to which the systems in higher education need to be rethought and redefined. The questions it raises are not new; they are simply more difficult to ignore.

The path to restoring the relevance of higher education runs through the future, not the past. Higher education must demonstrate, quickly and convincingly, that it is preparing students for the work and civic life that await them, a future in which GenAI will be as common as word-processing software. This moment calls for thought leadership, not gatekeeping. We must help students envision what AI inclusion should look like.

But helping students in this way reveals an uncomfortable truth: If what you teach—or how you teach—can be fully replaced by AI, perhaps it should be. For decades, colleges and universities have excelled at disseminating knowledge. However, in an era when AI can instantly generate content, quizzes, and even lesson plans, the challenge is no longer whether we should permit these tools in the classroom, but why our classrooms are so easily outpaced by machines in the first place.

Since the initial ascent of GenAI in late 2022, we in the higher education community have largely ricocheted from panic about the death of the college essay to promises about the potential to improve educational efficiency.^Footnote2 In recent months, the conversation has begun to settle—but only slightly. The question is shifting from "Should we?" to "How do we?" Answering that question demands nothing less than reimagining the core value proposition of higher education.

On many campuses, that reimagining is already underway. Some colleges and universities have begun offering GenAI tools and ramping up training for faculty, staff, and students. Indiana University (IU) is a case in point: The university now provides access to a broad suite of GenAI platforms—including Microsoft Copilot, Google Gemini, and self-hosted solutions built on open-source models. We recently announced a wide-scale, full enterprise deployment of ChatGPT to all of the university's 120,000-plus users (the second-largest rollout of OpenAI's ChatGPT Education to date).^Footnote3 Just as important, we have invested in helping our community build the skills to use these tools well. This includes GenAI 101, a free, self-paced online course available to all 90,000 IU students and all IU faculty and staff.^Footnote4 (In the first few weeks of the course, more than 27,000 students and 3,000 faculty and staff have engaged with it.) That course is complemented by additional trainings and resources, giving all users multiple entry points to develop both foundational digital literacy and practical GenAI skills.

Yet, deploying tools and offering training are easy. Even as higher education moves past the alarmed responses of ChatGPT's debut year, we've avoided more fundamental questions. As experts in educational technology, digital literacy, and organizational change, we argue that higher education must seize this moment to rethink not just how we use AI, but how we structure and deliver learning altogether.

Because ultimately, this is a cultural challenge more than a technical one. GenAI forces us to confront who we are, what we value, and how we can design learning that stays purpose-driven and people-centered. By exposing long-standing assumptions about assessment, pedagogy, and even the nature of expertise, it presents higher education with an ultimatum: reexamine your model or risk irrelevance.

Beyond Content Delivery: The True Purpose of Education

For centuries, colleges and universities have operated under an unspoken assumption: Professors transmit knowledge, students absorb it, and assessments confirm retention. From the "sage on the stage" to the expediency of Scantrons, we have rewarded recall over reasoning.

But when every piece of knowledge is one prompt away, these models become obsolete. If a machine can supply context on demand, then education must cultivate what machines cannot: application, synthesis, and problem-solving.

This moment is an opportunity, not a crisis. AI allows us to shift from product-based assessment to process-based learning. Instead of treating learning as an endpoint, where we evaluate the final artifact alone, we can now peer into how students think, evaluate, and iterate on their way to those artifacts.

Instead of capturing cheating, we should capture learning, shifting the focus from what students produce to how they engage with, refine, and apply ideas, as well as their reflections on why those ideas are important.

Let's explore a couple of examples. In journalism, AI can quickly generate a news brief, but it cannot interview a source, evaluate conflicting accounts, or determine what is meaningful or newsworthy for a particular community. That work—the judgment, curiosity, and ethical reasoning—is the substance of journalism, and that is where educators should focus. In teacher education, future teachers may use AI to draft lesson plans, but they must still decide how to differentiate instruction for students with diverse needs, create culturally responsive content, and assess the pedagogical choices that AI suggests. In both cases, the essential work—the learning—lives in human choices.

So, rather than banning AI, designing tests to "outsmart" it, or returning to bluebooks, we should embed these tools into our courses and require students to engage with them critically, ethically, and creatively. The AI Taskforce at IU recommended investing in this kind of "assessment innovation," which requires purposeful, reflective conversations with faculty.^Footnote5 We are supporting this work with our teaching centers by offering more assessment-focused programming and consultations.

When educators evaluate the quality of thinking, rather than the quantity of memorized facts or the final artifact, we can reclaim the purpose of higher education in an era where knowledge alone is no longer the primary currency. In doing so, we demonstrate to students and the public alike why colleges and universities are still relevant and valuable.

The Skills That Matter Now: Adaptability, Ethics, and Human Judgment

When we assess learning based on students' ability to think critically rather than on their Scantron test scores, we create space to cultivate capacities that machines can't replicate.

If GenAI can draft answers and summarize research, our standards must rise accordingly. Work that once merited an A should now earn a C. Excellence must be redefined upward, demanding not just accuracy but originality, ethical discernment, and the ability to frame and navigate complex problems.

That means doubling down on "power skills"—critical and creative thinking, ethical reasoning, problem-framing, and domain-specific judgment—delivered in a tech-saturated context. These durable competencies are precisely what current employer surveys flag as being in short supply.

AI doesn't render those skills obsolete; it makes them nonnegotiable. Students still need to be able to spot missing variables in a dataset, challenge the assumptions baked into the model, and decide when to override the algorithm.

Whatever the discipline—science, policy, business, or education—every meaningful project begins with framing the right problem. Inquiry, then, becomes the curriculum, pushing students beyond turnkey completion toward genuine understanding. At the core is human–technology collaboration. GenAI should be a thought partner, not a substitute for thought. Like any partnership, it depends on trust, responsibility, and purpose—hence the central role of ethics.

Ethical responsibility operates on multiple levels: helping students use AI wisely and preparing them to thrive in an algorithmic society, as well as in roles that have yet to be invented.

Ultimately, we must cultivate a culture, not just a code of conduct. The aim is to graduate students who can navigate ambiguity and shape emerging practices with confidence and conscience. So far, higher education institutions have focused on whether and how to use AI. Now, we must ensure that students learn to use it responsibly, guided by ethics, intentionality, and a sense of civic and professional duty.

The Changing Role of Faculty: A Positive Shift

The most disruptive gift that GenAI has provided us may be the opportunity to rethink the role of faculty. In an era when students can summon facts on demand, what they need from us is not more content but help navigating complexity, exercising judgment, and wrestling with ideas that can't be copied and pasted.

Some colleagues read that shift as a threat. It is anything but. This is an overdue invitation to trade "sage on the stage" for "partner in the process." Our value now lies in guiding students through ambiguity, critique, and meaning-making—skills a language model can only imitate. This type of mentorship has two parts:

• Elevating student work beyond the AI ceiling: If ChatGPT drafts the first pass, faculty should teach students to interrogate it, refine it, and push their thinking beyond what the bot can.
• Modeling ethical discernment: In an information glut, faculty should become curators of credibility and context.

GenAI also expands what our scholarship can do and who can benefit from it. Research that has been locked behind paywalls can be translated—literally and figuratively—into podcasts, explainer videos, simulations, and community tools. A literary scholar might turn genre analysis into a reading group guide. A public-health team could convert policy findings into a multilingual TikTok series. These formats aren't just ways to disseminate research; they're public scholarship at scale, emerging precisely when higher education needs to rebuild trust and expand its influence.

Reimagining our roles in this way will also require working in community—across disciplinary and organizational silos—to explore not only how we teach, but how we engage with the wider world. At IU, we're fostering this through a new GenAI Faculty Fellows program, which drew about 140 applications and led us to nearly double the size of the first cohort.

The point is relevance, not replacement. Faculty are more critical than ever, but they are needed as guides, collaborators, and public intellectuals—not gatekeepers.

What We Need for the Future: Bold Action, Not Complacency

Higher education has spent two years reacting to AI. The time for reaction is over. The time for leadership is now, and it requires three decisive actions:

• First, assessments must be rebooted to prioritize process over product, reflection over recall, and application over answers.
• Second, durable skills such as critical thinking, creativity, and ethical judgment must be foregrounded and explicitly taught in conjunction with AI, rather than despite it.
• Third, faculty must shift from being transmitters of information to mentors who coach students in synthesis and responsible technology use.

Institutions that act on these recommendations will define the next chapter of higher education. Those that cling to 20th-century models will watch their relevance erode. So, let's stop asking, "How do we fit AI into the classroom?" and start asking, "How can AI help us reimagine learning and regain public trust?"

We need new norms, new language, and new paradigms, and we need them now. AI will not replace colleges and universities, but it will expose the aspects of higher education that no longer serve our students or society. What we do next will determine whether we remain vital or make ourselves obsolete by our own design.

Notes

1. Jeffrey M. Jones,"U.S. Confidence in Higher Education Now Closely Divided,”Gallup, July 8, 2024; Richard Fry, Dana Braga, and Kim Parker, "Is College Worth It?" Pew Research Center, May 23, 2024; Intelligent.com, "Nearly Half of Companies Plan to Eliminate Bachelor's Degree Requirements in 2024,"press release, July 23, 2024.Jump back to footnote 1 in the text.↩
2. Stephen Marche, "The College Essay Is Dead,"The Atlantic, December 6, 2022; Tanya Milberg, "The Future of Learning: How AI Is Revolutionizing Education 4.0,"World Economic Forum, April 28, 2024.Jump back to footnote 2 in the text.↩
3. Justin Whitaker, "IU Community to Get Access to ChatGPT Edu,"IT Today, August 28, 2025.Jump back to footnote 3 in the text.↩
4. Indiana University, "IU Launches Free GenAI Course for Anyone with an IU Login,"press release, July 22, 2025.Jump back to footnote 4 in the text.↩
5. Indiana University Generative Artificial Intelligence (GenAI) Task Force Report,(Indiana University, March 2024). Jump back to footnote 5 in the text.↩

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Adam Maksl is Professor of Journalism & New Media and Chair of the Department of Communication at Indiana University Indianapolis. He previously served as Senior Faculty Fellow for GenAI Learning Innovation at Indiana University.

Anne Ottenbreit-Leftwich is Associate Vice President for Learning Technologies at Indiana University and Barbara B. Jacobs Chair in Education and Technology and Professor of Instructional Systems Technology at Indiana University Bloomington.

Justin Hodgson is Strategic Director of GenAI Faculty Initiatives and Director of the Digital Gardener Programs at Indiana University. He is also Associate Professor of English at Indiana University Bloomington.

Kevin J. Jones is AI Strategist and Associate Professor of Management at Indiana University Columbus.