As a curriculum researcher, I believe AI will catalyze significant but evolutionary change in universities rather than fundamental disruption. While AI enhances pedagogical delivery through personalized learning and accelerates research through data analysis, the core functions of universities—critical thinking development, knowledge creation, and scholarly discourse—remain distinctly human endeavors. The key lies in thoughtful integration that augments rather than replaces human-centered education, requiring adaptive curriculum design to prepare students for an AI-collaborative future.

Dear Nyamdavaa Byambadorj , AI will free up professors from routine tasks so they can focus more on mentoring and creative teaching. In the classroom AI can personalize learning and spark deeper engagement. In the lab AI speeds up data analysis and opens new paths for collaboration across disciplines. Universities that partner with AI tools will evolve into even stronger centers of innovation and human-centered education.

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In my opinion, AI is revolutionizing the manner in which universities educate and conduct research by facilitating personalized learning and accelerated data analysis. However, the very essence of universities goes beyond the transmission of facts. And also, they foster critical thinking, ethical thinking, and human interaction. While AI necessitates concerns over academic integrity and reliance, it is perhaps best considered as a tool that will change but not replace universities, forcing them to innovate while retaining the human element of their mission.

That’s a really important question—one I care deeply about, both as someone who works in math education and as someone who studies how AI is changing the way we learn.

After years of watching how tools like AI reshape classrooms and research labs, I believe AI won’t just be another gadget professors tuck into their teaching toolkit. Instead, it’s going to push universities to rethink their very purpose—in both teaching and research. And honestly, that’s not necessarily a bad thing.

Let me explain by looking at two big areas: teaching and research.

1. Teaching: It’s Not About Delivering Facts Anymore

For a long time, universities were places where professors taught students by sharing knowledge—lecturing, assigning problems, grading exams. But now, AI can do a lot of that faster and more personally: it can explain concepts, generate practice problems, give instant feedback on math homework or code, and even draft essays.

So if AI can handle the “what,” the university’s real value has to shift to the “how” and “why.” Instead of just filling students’ heads with facts, we need to help them become thoughtful, critical learners—people who can ask good questions, spot flaws in reasoning (even in AI’s answers), and think for themselves.

In my own math classes, for example, I’ve stopped giving standard problem sets. Instead, students work on open-ended projects where they use AI to explore ideas—but then they have to explain their thinking, question the AI’s suggestions, and draw their own conclusions. The classroom becomes less about getting the right answer and more about learning how to navigate uncertainty, collaborate, and think ethically.

And that means we also need to rethink how we assess learning. If AI can write an essay or solve an equation, then grades shouldn’t just reward the final product. We need to value the process—the originality, the reasoning, the honesty.

2. Research: AI as a Partner, Not Just a Tool

AI is already changing how discoveries happen. Think of breakthroughs like AlphaFold predicting protein structures or AI helping prove mathematical theorems. In many cases, AI isn’t just speeding things up—it’s suggesting new ideas or spotting patterns humans might miss. It’s becoming a kind of research partner.

But that raises tough questions:

• If an AI helps make a discovery, who gets credit?
• How do we trust results when we can’t fully understand how the AI reached them?
• Will this tech help smaller universities catch up—or just give more power to well-funded labs and big tech companies?

Universities now have a new responsibility: to set clear standards for how AI is used in research, to teach researchers not just how to run AI tools but how they work (and where they go wrong), and to make sure these advances benefit everyone—not just a few.

The Bigger Picture: What Makes Universities Irreplaceable

At the end of the day, AI is amazing at processing data and optimizing solutions—but it doesn’t care about truth, justice, beauty, or meaning. Those are human concerns.

Universities aren’t just information warehouses. They’re communities where people come together to ask hard questions, wrestle with ethics, and figure out what knowledge is for. That’s something AI can’t do—and never will.

So yes, AI will change universities—deeply. But not by making them obsolete. Instead, it’s giving them a chance to double down on what they do best: helping people become wise, thoughtful, and responsible thinkers in a complex world.

The universities that succeed will be the ones that see AI not as a threat, but as a challenge—to become more human, not less.

Certainly, yes. AI is already bringing fundamental changes into the process of teaching and learning: professionalizing and making it easier and interesting. However, AI should be used as an aid tool and cannot totally replace human contributions.

On one hand, AI is "digitalizing" the education system at the university level. Lecturers are incorporating AI in creating slides, lecture notes, graphics and so on, making their presentations look "more creative" than their original work. On the other hand, AI is hindering creativity of learners and lecturers as most of us use AI as a shortcut. For instance, suppose i want a short python or java code, I would just prompt the AI to give it to me without extended research about the code. AI lacks human contact and therefore may be difficult to change role of universities in teaching and research. A combination of human contact with AI may do better!

As a university academic, I see AI neither as a passing gadget nor a wholesale replacement—it’s becoming the substrate of scholarship. Its promise is real: sharper tutoring, faster literature synthesis, new research pipelines. But the value of universities will hinge on what we add to AI: cultivating judgment, ethics, methodological rigor, and communities of inquiry. If we redesign assessment for process and provenance, teach AI literacy and attribution, and govern data responsibly, AI will amplify our mission; without those shifts, it risks eroding trust and flattening learning into mere output. The future is human-led, AI-augmented.

About AI transforming or taking up the role of Universities in research and academics, I should say, yes and no.

No, AI is a valuable tool for use in academia because it simplifies work, not by replacing our efforts and abilities to think, reason, and perform work, but as a complementary tool to what we do. Many a time, AI has provided faulty or questionable responses because it lacks the human abilities to think, synthesize, and scrutinize what it finds in the cloud. As a result, the best user of AI should be the best learner or academic, not an amateur regarding the information he or she is looking for.

Yes, if students and academics make use of AI with the thinking that it alone must provide all the desired knowledge. It will be disastrous to stop thinking and depend on the brainless tool to think on our behalf. A tool without the ability to discern fully between right and wrong, but dependent only on the instructions it feeds on.

Researchers and all other academics should understand the fact that these tools depend on humans who feed them with the different codes of instructions they utilize. It is also important to understand that the cloud has both right and wrong information. Information that has been peer reviewed and that which hasn't been reviewed. But all this is at AI's disposal, and can be unleashed depending on the researcher's input query.

Yes, probably AI will fundamentally change universities structure of education by making teaching more personalized and research more collaborative and data-driven. Tomorrow, Universities will shift from information delivery team to developing critical thinking and problem-solving skills body. Also, the Administrative tasks and assessments will be automated, increasing efficiency as per the dynamic changes. Additionally, AI-powered tutors will support students 24/7, enhancing engagement and curiosity interaction. Research will become more interdisciplinary and powered by AI analysis and tabulation . Institutions that ignore AI risk falling behind in relevance and modifications . Ultimately, AI is becoming central to the university mission—transforming both teaching and research which will definitely have good impact.

Interesting question and replies.

AI will sure bring changes with opportunities and challenges. Higher Education is not exception.

Before the AI, youtube is a global universty. Students who wants the improving any domain can use website. And yes I belive too, AI will change the universty role in depth. Actually for this centry universties must convert themselves.

Yes, AI will change the role of universities, but it won’t replace them.

• In teaching, AI can already explain concepts, generate exercises, and guide students. This means lecturers will focus less on just “delivering content” and more on mentoring, encouraging critical thinking, and shaping students’ character.
• In research, AI speeds up data analysis, literature review, and even writing. But universities will remain important in checking accuracy, ensuring ethics, and guiding how knowledge is used responsibly.
• As institutions, universities will still matter because they give credibility, provide a space for debate, and build human values that AI cannot.

So, the university of the future will not just be a place to get information, but a place to learn how to think, create, and act responsibly in an AI-driven world.