Week 8: The Future of AI
AI literacy essentials for academic libraries
Choice and Clarivate have teamed up to develop an eight-week, newsletter-based course on generative AI literacy for academic library workers. If you are AI curious—and short on time—then this course is for you!
Each week contains three sections:
- Introduction: An overview of a core AI literacy competency
- In Practice: An interview or case study
- Reading Room: Further reading material focused on the topic
- The module closes with a quiz and discussion questions.
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In week eight, we look ahead to the future of AI.
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Table of Contents
Introduction
The Imagination Lab: Why Libraries Must Lead in the Age of AI
by Kyle Bylin, Research and Assessment Librarian at Saginaw Valley State University
A few months into my first year as a university librarian, I found myself sitting across from a first-generation student at the campus Starbucks, talking about what it means to become a librarian in 2025. As we chatted, I realized the truth: the library profession he wanted to be a part of is already being fundamentally remade by artificial intelligence. And that disruption is happening far faster than most of us want to admit.
Where librarians once served as the primary guides to knowledge, AI tools like ChatGPT, Consensus, Semantic Scholar, and a rapidly growing ecosystem of “agentic” services now answer the very questions that used to bring students and faculty to our desks. They summarize research, generate citations, synthesize sources, and can even draft research papers in moments.
The implications for libraries are profound. The value we provide can no longer rest on access alone. What matters most now isn’t curating the best bibliography or teaching students how to find information in a database. It’s empowering them to frame more original questions, make catalytic inquiries, and develop the capacity for sense-making amid overwhelming abundance. In this new age of intelligence, the most precious commodity is not what you know, but how you ask. The librarian’s role, once defined by mediation and retrieval, is shifting upstream to the domain of question design, critical thinking, strategic foresight, and systems navigation.
The problem is that higher education is still mostly stuck in yesterday’s paradigm. Much of what is branded as “AI literacy” is little more than crisis management—reactive workshops about academic integrity and the perils of AI cheating, policies about proper citation, or cautious introductions to chatbots that have already been leapfrogged by the latest model release.
These are important, but they are quickly becoming table stakes. What we need is a leap toward AI fluency, and ultimately, mastery: the ability not just to use these tools, but to collaborate with them, to shape them, to direct their generative power toward genuinely meaningful discovery and creation.
That means helping students and faculty get comfortable with iterative prompting, evaluating, and refining AI outputs, and pushing these systems past the surface and into real insight. It means moving beyond suspicion and fear and helping our communities discover new forms of inquiry, creation, and communication that were previously unimaginable. If we succeed, the outcome will be more than just students “cheating better.”
The most radical possibility is that students become so adept at framing problems, using AI for deep research, and synthesizing and presenting their findings in creative, multimodal ways that the traditional assignment itself—the research paper and presentation deck—becomes obsolete and is reinvented anew. Our mission should be to help students transcend the boundaries of academic integrity, not just police them. We must help them grow into professional roles that haven’t even been invented or named yet.
New Roles for Academic Libraries
Academic libraries should become imagination labs—places where students, staff, and faculty don’t just access knowledge, but experiment with its synthesis and creative expression. Libraries are not just quiet warehouses of books or digital repositories—they can be vibrant innovation and creative studios equipped with the latest generative tools and other emerging technologies, where interdisciplinary teams reimagine research as a public, performative act.
Imagine a student using agentic AI to perform a literature review in minutes, then transforming those findings into a podcast, an infographic, or a video essay. Picture business students simulating market disruptions using agentic AI models, or history students building virtual timelines and documentaries from archives. The librarian’s role is evolving into that of a trusted guide, coach, and catalyst—helping people move from curiosity, to creation, to impactful communication.
This isn’t some distant dream. We could build a minimum viable prototype with just a handful of laptops loaded with premium AI subscriptions, offered as part of hands-on workshops in classrooms or in our active learning space. We could teach students to use these tools not only to answer questions, but to frame them, iterate, and design their findings for real impact.
Libraries are uniquely suited to this work. We are among the few entities on campus able to bridge disciplines, convene diverse teams, and act as neutral ground for innovation. The next chapter of library leadership won’t be written in circulation statistics or database logins, but in our capacity to pilot and scale new forms of AI-enabled learning and creation.
To do this well, though, we need to move beyond semester-by-semester thinking and start planning with strategic foresight: What will academic research, instructional sessions, and civic life look like in 2030? What skills and frameworks will our students need to thrive? How do we ensure our own communities are not left behind as the intelligence gap grows wider?
Setting up Our Own Imagination Labs
Above all, we need to become proactive, not reactive. The window for libraries to shape the future is closing. If we do not lead the charge on AI literacy, fluency, curiosity, and creative imagination, technology companies and for-profit alternatives will fill the gap. If we stay defensive—if we double down on outdated workflows—we will be left behind, not by accident, but by design. We must be coalition builders and systems architects, working with faculty, local employers, and our communities to ensure that our graduates are not just AI users, but AI innovators, leaders, and ethical stewards.
If you had to launch your own imagination lab tomorrow, with nothing but a shoestring budget and a handful of allies, what would your first 90 days look like? Who would you invite to the table? And how will we know if we are truly building the future that higher education—and our communities—deserve?
In Practice
What’s Next for AI in Scholarly Communication?
Technology evolves quickly and progress with commercial AI applications for general consumers has similarly proceeded apace. In fact, as we were planning this series of educational modules, we knew that concepts like prompt engineering and other text and image-based interactions with GenAI models were becoming old news. Even so, AI applications in academia have benefitted from a more cautious approach. Vendors are taking care to ensure their products don’t circumvent critical thinking, research integrity, and trust in source materials. And even as AI continues to evolve, this same attention to detail remains. For this final module, we sat down with Oren Beit-Arie and Drew Freisthler, Clarivate’s Senior Vice President of Strategy & Innovation and Senior Director of Engineering, respectively, to talk about what new capabilities are on deck for the scholarly communication pipeline. The big takeaways? Agentic AI and much better interactivity.
Click here to read more about where AI in academia is headed.
What will be the next significant jump forward for AI during the next year? What new features will be introduced in research workflows and scholarly communications?
Oren: The shift to agentic AI is very significant. It’s about an opportunity to move beyond what we’ve seen in the first wave of GenAI, which was more conversational and chat-based, and toward agents that are much more proactive and, in fact, interactive. They reason, they plan, they execute, and they do that in multistep, complex tasks and workflows.
We’re seeing this in two areas. One is to push productivity and process efficiencies using agents. This is happening in scholarly communication throughout the lifecycle—in publishing, peer review, and the production of research.
But it’s not just about saving time. It also increases volume and quality. When we think about a lot of the administrative tasks that are done in higher education—and many of them are mundane tasks—I think agentic AI is going to prove very effective in helping do more and at scale and, in many cases, at very high quality.
Second, and maybe even more importantly, agentic introduces an ability to solve new challenges that we couldn’t solve before or were too expensive. In molecular biology, for example, we see advancements in fields like genomics and in mRNA studies that can advance research in a significant way.
And, of course, all that needs to happen in the framework of keeping the integrity and the ethics of both pedagogy and research.
With the rise of these technologies, we believe there’s going to be an increased focus in grounding outputs in trusted sources. We’ll see more focus on academic-specific solutions with more reliance on mechanisms such as Retrieval-Augmented Generation (RAG) models.
And I also expect that we’ll see more partnerships with technology companies and the LLM providers. The intention is to meet users where they are—meaning, they can start their learning or research journey directly in the apps they already use, whether it’s ChatGPT, the LMS, or Google Scholar.
What priorities are content and tech providers like Clarivate focusing on?
Oren: In terms of our priorities, it’s about research and pedagogical integrity by design. Building transparency, explainability, confidence, and trust with AI is a major focus for us.
We also want to offer the flexibility to create a framework for customers and users to develop and adapt AI to meet their needs and use cases. There will always be use cases that we haven’t thought about. We are creating solutions based on AI and agentic AI, but we also want to give institutions, librarians, researchers, administrators, and students the tools to use responsible AI too, so they can adapt and create their own agents. We’re building what we refer to as Agent Builder.
Drew: We’re talking about agents that can make API calls to integrate services in ways that we’ve never been able to do before. Just imagine what libraries are going to be able to do when various vendors have various APIs that can be used together. They’re going to be able to make products out of different tools from different vendors and produce these things along with all the assets the library has. It’s really an exciting space. The synergies we haven’t been able to realize for various technical reasons? Those barriers are coming down.
So imagine you’re trying to create a client-facing service and you want to use your LibGuides from Springshare and your local results from Primo discovery. You could build something that allows them both to communicate into one single chatbot—or three or four other things, or ten other things. You’ll be able to take those vast resources and plug them into an agent in a way that it knows how to communicate to those various APIs, interpret the results, and feed those to different places or intermingle them and do things on your behalf.
It’s not about purchasing new assets. In fact, vendors will enable these capabilities to communicate in agent frameworks. These sorts of things will speed up processes for librarians trying to automate services and patrons trying to complete tasks.
Are vendors communicating with each other about these APIs that are connecting different tools? Do they even need to?
Drew: With the standards that are starting to emerge, we don’t have to. But we do need to conform to a way that enables an agent framework to talk to those various tools and then those tools will describe their various API endpoints, what parameters they have, when they should be called, and so on. I don’t have to talk to Springshare’s engineering staff because they are going to surface the APIs—they already do. And we would surface our Primo APIs, which we also already do. But it’s the agent framework that lets you communicate with both of those and put the results together and run searches as necessary. Or ProQuest or Elsevier or anybody else. So that’s where we see the future going. All of these assets are going to start playing nicely together. Standards are already being adopted, with Model Context Protocol (MCP) emerging as a key one. MCP creates a common way for agents and tools to share context and data, so different systems can interoperate more reliably.
Oren: We are already seeing this interoperability internally. We can create solutions now that go across multiple areas of our business. Technically, there will be standards that govern [these activities], and we still need to respect each other’s businesses and do this in a collaborative fashion. I think that the most important point here is this is going to help scholarly users do more and de-silo some of the things that are currently siloed to specific applications.
What are areas that library and academic leaders should be paying special attention to in the next 12 months?
Oren: Education is key; building skills. There is a lot of concern about what AI brings. Certainly there are a lot of opportunities for bad actors, but there are also huge opportunities for accelerating both the productivity and quality of output and outcomes. But it all starts with education. Teaching information literacy that is tailored to the age of AI is critical. There are a lot of components there: how to evaluate AI, how to evaluate tools, understanding how we apply our ethical, pedagogical, and research integrity, but it all revolves around education.
The other point is change management. There is a lot of skepticism, concern, and even resistance, but we need to recognize the sheer fact that everyone is using AI. We have to handle that change, manage that change.
How do you see agentic AI impacting the idea of human-centered scholarship? And how are you reflecting this in the construction of your AI-enhanced products?
Drew: It’s similar to how we’ve done things in the past. When we develop a new agent, our product team will build user stories. That comes from interviews with users they will have to work with. Then we can use those stories to generate the first versions of our system prompts.
Most of the agents we’re building these days are very human-focused. They need an awful lot of interaction to get from a starting point to an end goal—whether that’s a literature review or resource cataloging. There’s a lot of back-and-forth [with the agent] before it actually generates the results.
We try to focus on making task-specific solutions, which does a couple things: It takes a lot of interaction to get to results and, more importantly, we put in a lot of guardrails. The [agent is] not allowed to go out of its specific purpose. So if you ask it to do something it’s not supposed to do, like write an essay, it’s going to say, ‘No, sorry, I’m just here to help you understand this document and generate the key points for your research.’
We focus on building out test cases, which we can rerun and then try to improve them. So, over time, we get better and the models get better. But it starts with capturing the user stories to find a narrow focus for the agent and then work from there.
Oren: The last point to make here is the importance of working as a sector. For us, it’s working as a community and we have different forums and channels for that. We have user groups, development partnerships, design partnerships, and we are also working with an AI council that provides guidance and advice. One of the things we found helpful is to look at AI as a fundamental infrastructure component. So when Drew is talking about guardrails, this applies to everything that we do. It’s not product by product, it’s at the infrastructure level, making sure we address that and have the proper governance around that. But a key factor here is the partnership with our community through the various channels, to keep asking the tough questions and iterating around those issues.
Reading Room
A selection of multimedia content to fit your time commitment.
5 minutes
- Harnessing the power of AI in academic libraries. Ex Libris, 2025.
- MCP Explained: The New Standard Connecting AI to Everything, by Edwin Lisowski. Medium, 2025.
- Enhancing Your Understanding of Agentic AI: A Practical Guide. Stanford Engineering Center for Global & Online Education.
10 minutes
- Getting Ready for the Future: Teaching AI in the Library, by Ann Baillie. ALSC Blog, 2025.
- How we built our multi-agent research system, by Jeremy Hadfield et al. Anthropic, 2025.
- Artificial Intelligence (AI) and Academic Libraries, by Jeehyun Davis. College & Research Libraries News, ACRL, 2024.
- Navigating the Future: Key Trends in Academic Libraries for 2024, by Lily Ko. IFLA Blogs, 2024.
- AI Literacy: A Guide for Academic Libraries, by Leo Lo. College & Research Libraries News, ACRL, 2025.
20+ minutes
- The transformative potential of Generative AI in academic library access services: Opportunities and challenges, by Frank Boateng. Information Services and Use, 2025.
- How AI Will (and Won’t) Impact Library Work. The Authority File, 2024. Podcast.
- 2024 EDUCAUSE AI Landscape Study, by Jenay Robert. EDUCAUSE, 2024.
- Pulse of the Library Report 2024. Clarivate, 2024.
Quiz Time
Test your AI literacy knowledge!
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Discussion Questions
AI gives us a lot to think about. Share your thoughts in the Leave a Reply section below!
- What do you think is the future of AI in higher education?
Take me to the Table of Contents.
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38 responses to “Week 8: The Future of AI”
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Artificial intelligence (AI) is a fascinating and rapidly evolving field, with new developments emerging every day. The future of AI is expected to be transformative, creating significant opportunities across many sectors. In higher education, AI holds great promise for enhancing teaching, learning, and research. However, universities must ensure that AI is used ethically and responsibly. It should serve as a tool to support educators and students, rather than replace human intelligence, critical thinking, or academic integrity.
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Higher education will continue to advance digital learning options and AI-infused practices. We will evolve with technologies and tools as we always have. However, the personal connections, the genuine learning experiences, and the human-centered approaches we have created for learners on our campuses will become even more valued and important in an increasingly digitized world.
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The emergence of artificial intelligence (AI) technology has opened new avenues for enhancing theological education in Christian contexts. Asia-Pacific Nazarene Theological Seminary (APNTS) and how students and professors are adopting and integrating these changes. In line with these adaptation, we as seminary librarians must be vigilant in being Ai literate to be able to fully balance Ai tools and the challenges of these utilities.
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I think that AI will become a critical part of higher education. Not only because it will become ubiquitous in other parts of our lives but also because it will become a tool that can be used to increase the pace of research endeavors in both the sciences and classic liberal arts fields. Researchers of all levels will be able to synthetize knowledge into manageable pieces that can assist at every level of the research process. The important thing is, as mentioned several times in this course, to teach how to use AI ethically and encourage AI literacy among all individuals.
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What do you think is the future of AI in higher education?
I remember when the internet came along and how it changed the library as we knew it. Some of the predictions came true and the same will happen with AI. Does AI complicate the research landscape and make information literacy even more challenging for students? Yes, it does but they said the same about the internet. I think that we as librarians have to be engaged and be cautiously optimistic. -
AI is rapidly growing, with new models emerging and expanding their capabilities every day. The future will bring more of that, so it’s important for us to keep embracing the changes and finding better ways to use these tools. If we let AI handle some of the routine or mundane tasks, we can spend more time focusing on innovation, research, and the future of education. When used the right way, AI can be an incredible support for both learning and discovery.
AI literacy will move beyond just learning what AI is and how it works. It will focus on critical thinking, evaluation, and developing real fluency in using these tools to find information and create new things. The students learning AI literacy now will be the ones who figure out how to address environmental and ethical concerns around AI. They’ll need to know how to use it responsibly in their classes and careers.
Libraries have always played an important role in helping students and faculty adapt to new technology, and that won’t change with AI. While I think AI will have a lot of positive effects, it might also change the roles of librarians and instructors in ways that feel challenging. Still, we’ll need to keep showing our value and adapting so that AI becomes something that enhances our work, not something that replaces it. -
While I still think that information professionals should be more focused on ethical guidelines, policies and governance associated to AI then this definitely will change the spreading of inaccurate information and widening the digital divide.
While we can agree that AI tools and applications are here to stay and more innovations will continue to come up. In my view, the increased diversity of information through the internet will need to have Agentic AI for searching, discovery and sematic scholarly to help in institutions and organizations on electronic resources and a source of knowledge creation. -
My hope is that the future of higher education in AI is a collaboration between human creators and thinkers and AI agentic agents. I’m hoping that AI becomes super-coaches that can produce individualized learning and instruction for each human. Any success in this aspiration must be predicated upon the human production being the default and desired output of any AI/human collaboration. Even though the AI agentic agent can “think” and “reason” better the human, its programming must always default to the “do no harm to human or any animate mammal.” Then the technology has a chance of being the beneficial tool its creators promise. I also hope the LLM for education becomes trained with wider academic content. I would love for it to have all data, rather than edited LLMs. I want it especially to hold languages from vast ethnic groups so that they are not lost and can be taught to and learned by future generations. I do believe that AI agentic agentis can eventually replace some types of instruction. It can be trained to be more patient, less judgemental, and customizable to all types of learners. Even though these agents do stand to replace some humans, which does stand to be difficult for the humans.
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¿Cuál cree usted que es el futuro de la IA en la educación superior?
Los estudiantes y docentes se enfocaran en aprender y enseñar mucho de la IA, sera su herramienta principal para estudio y trabajos y consultas, los estudio por parte serán dinámicos, y para los estudiantes que tiene problemas para estudiar podría ser un refuerzo muy viable y sus tareas serán más fáciles. -
What do you think is the future of AI in higher education?
Instead of what I think, I will put what I would hope. I hope that agentic AI will make searching for research more intuitive. Working as a reference librarian, I can see firsthand how not understanding the little tricks we use impedes the average user’s ability to locate materials, and in their confusion or frustration, they resort to “it is so much easier to just do a Google search.” Users see the value of peer reviewed resources, but sometimes getting there can frustrate beginning attempts at research. As much as I love the “ah-ha” moment of teaching, I worry about all the others I was unable to reach when they needed help.
I hope that AI skills will be worked into my institution’s information literacy classes so that we can contribute to students’ and faculty learning about AI. It seems that fear and anger are more likely the prevalent feelings when I talk to library staff and humanities instructors. As long as we stay secretive and hush-hush about mentioning AI, the more students may use those attitudes to duck their responsibilities for learning. We won’t be able to explore a partnership between responsible usability and transparency in the academic realm if we are hiding from it. We need to magnify the human factors of AI with the leadership of knowledgeable users.
I hope that all users of AI will consider their hand in regard to privacy, ethics, and environmental impact. We need a better framework for solutions.
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Honestly, the future of AI in higher education is going to be the same as every other supposed labor saving ed tech of the past several decades.
It’s going to be a legacy of layoffs and downsizing, the elimination of departments and roles, and those who are left are going to have to be doing even more tedious labor and facing even more burnout as they are expected by administrations to manage both their growing class sizes and the technologies that are being foisted on faculty without any input from that same faculty.
The logic of the neoliberal university that seems to forever be crying poverty and austerity when it comes to funding teaching positions and support staff but can find endless funds for shiny new tech is to constantly apply every supposedly labor saving technology in the most exploitative and cost cutting ways.
This technology, if it’s foothold is allowed to grow, is going to usher in a whole new wave of immiseration in higher ed that is going to leave both our scholarship poorer and our students wondering ever more if a college education is worth the price on the tag. Our already overworked adjuncts will be fighting for fewer and fewer roles, just as we’re seeing happen to our computer science students entering the work force today. The positions that will be available for promotion and tenure will dry up, and the full time faculty that remain will be overworked, underpaid, and tasked with overseeing the last vestiges of higher education undermined.
The promises of this technology have largely been overblown, but when management can say it’s good enough they will. Allowing this technology to dictate the future of higher education is going to mean a lot of people are going to suffer as a result, everywhere from the academe and at the imperial margins.
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AI in the academic setting is just getting started. It changes so rapidly that it will be on the teachers, Libirans, etc. to keep up with and to help the students when needed.
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I would like to sincerely appreciate the opportunity to take part in this 8-week AI course. The program has been both insightful and transformative, offering me a solid foundation in understanding artificial intelligence and its practical applications.
Over the past weeks, I have gained not only theoretical knowledge but also hands-on experience that has expanded my perspective on how AI can be applied to real-world problems, particularly in the library and higher education in general. The guidance, resources, and support provided throughout the course have been invaluable in shaping my skills and confidence in this field.
I am grateful to the instructors and facilitators for their dedication and for creating an engaging learning environment. This course has sparked my curiosity to continue exploring AI, and I look forward to applying what I have learned in future projects and endeavors.
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What do you think is the future of AI in higher education?
AI is continuously evolving and may be a bit difficult to correctly pinpoint how the future of AI will look like in higher education. speculatively i would say the future of AI in higher education will be Agentic AI because of its ability to not only respond but reason, plan and take actions without hallucinations. Agentic AI utilizes retrieval-augmented generation, allowing the model to access external databases for more accurate results. -
What do you think is the future of AI in higher education?
ai is part of higher education. need to join ai and not be afraid of it. it is the future and the present of education, not a replacement. teaching the uneducationed young generation how to think critically and not just give the information and that is how we as librarians/information specialists can embrace ai tools for ourselfs amd our customers -
The future of AI in higher education will continue to evolve as AI evolves. The future cannot be correctly predicted at the moment. However, this unpredictable future will continue to shape the roles of librarians in academic libraries. This implies that we’ll continue to see the roles of librarians evolving until generative AI reaches its elastic limit in the year X where X is currently unknown.
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What do you think is the future of AI in higher education?
This course taught me that the future of AI is promising. It gave me essential skills that I can use as a librarian and I will share everything I have learned with my colleagues. Librarians are here to stay and AI will enhance how we deliever services to our users. I have so much to share in the form of workshops on how to use GenAI effectively, evaluation, prompt engineering, formation of CoPs, AI future trends that can assist the library users when doing research etc. Thank you for offering this AI literacy essentials for free. -
…the future of AI in higher education?
Well, the future is being defined and clarified. I’m not worried. There are many working on it!What does make me think… again! It’s about my environment, research and graduate studies. They generate knowledge! How can I support inventiveness and creativity?
This situation motivates me to reason-discern-choose-test-evaluate and start over; to use what I naturally have. I learned computing at the blackboard… and I’m still here… Of course I can continue interacting as a LIS professional, with engineers and scientists of any specialty!
It has been a pleasure to be with you and learn from you for 8 weeks. Thank you all!
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I think the future of AI in higher ed is about teaching communities how to work with AI without anthropomorphizing it, without offloading critical thinking skills to it, and to not automatically go to it as the first tool. It’s about teaching communities to engage critically and show how the tools can be used responsibly and ethically to become more efficient while always remembering to evaluate and verify results, no matter the platform.
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What do you think is the future of AI in higher education?
I feel that we are still in the early stages of understanding this new phenomena but AI is already impacting and will continue to impact both higher education and academic libraries.
Our library is already using AI, integrating it into our workflows, digitising repositories and collections, providing personalised recommendations with searches and enhancing research support and accessibility.
While AI has the potential to further improve accessibility and information retrieval, to provide personalised learning and 24/7 support for students as well as to improve collection development and management, there are, however, concerns that need to be addressed. These issues revolve around the accuracy, credibility and quality of generated content, the issue of data privacy and security as well as ethical breaches and potential bias. Technical considerations include the scalability and interoperability of systems and then there is the cost and the financial challenges that the adoption of an expensive new technology involve. Another important consideration is the reskilling and training of library staff to increase “AI literacy” and reduce “AI fear” so that the new technology can enhance organizational efficiency.
AI is a new chapter in the development of library services and I think it should be embraced, helping our students to use it ethically to assist their studies while being aware of the environmental impacts and consequences.
I have found this course an excellent and very helpful introduction to the topic. Thank you. -
I found the course very interesting and useful. As regards the question about the future of AI in Higher Education
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What do you think is the future of AI in higher education?
I think that there is a future, obviously, of AI in higher education. AI is already showing itself to be a useful tool for research and learning. However, AI is will not be the end-all of research and learning in higher education. AI will be absorbed into the fabric and structure of higher education, but not the other way around.
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AI is here to stay. What libraries need to do is embrace the possibilities that AI presents to help with the manipulation of data. It means that Librarians must retool themselves. While the core functions such as cataloging, referencing and acquisitions are still valid the processes can be enhanced with AI. It has become more important now to teach responsible use of AI to students and staff. As usual keep up with the latest technology trends.
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From my perspective, AI is likely to become a tool that supports, rather than replace, the core goals of learning. I think we’ll see it used more and more to handle the routine, time-consuming tasks that often weigh students and faculty down: things like summarizing large amounts of information, generating practice problems, or helping students organize their research.
At the same time, I think its real potential lies in making education more personalized. AI can help students get feedback right when they need it, or point them toward resources that match their learning style. For faculty, it could surface trends in how students are doing, so they can adjust their teaching in real time.
That said, I also believe higher education will need to approach AI carefully and thoughtfully. We’ll have to keep asking hard questions about accuracy, privacy, and equity. For example, the funadmental questions of who has access to these tools? How do we make sure they’re supporting critical thinking, rather than truncating it?
So, to me, the future isn’t about AI replacing human educators or the human side of learning. It’s about finding ways to use these tools to enhance curiosity, creativity, and access, while holding on to the deeper values of education that AI can’t replicate.
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The future of AI in higher education is transformative. As AI changes and expands, so must those using it, and it enhances what we are doing.
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There’s no going back now; as librarians we must adapt. I can’t help but think, though, that there’s always a bigger fish…that one day technology will come along to render our current AI obsolete, and we’ll have to learn and adapt all over again. Even as the nature of our field of information science is “the only constant is change”, so, too, is the nature of information science cyclical. Humans are curious; they want to find out; they build a tool to help; they figure something out; then they are curious again when the new tool and the new information, and the new way of thinking, get tired and old. AI won’t solve all our problems; it will be a tool we use to look at them in another way (until we get bored & make a new tool).
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The good news: AI will open vistas we cannot imagine.
The bad news: AI will open vistas we cannot imagine.
All joking aside, I think AI will follow a similar pattern as other powerful technology in our society. The telegraph, telephone, automobile, PC, and internet all raised social concerns upon becoming widely available. I arrived in the library cosmos in 1999 during much hand ringing about the internet and all the things it was going to replace: books, magazines, libraries, and librarians. Some of which came to fruition and some did not. I believe the same will be true of AI. I do not believe the Terminators will be showing up anytime soon. -
Ideally, AI in higher education will be more of an assistive tool for educators, students, and librarians for specified tasks and automation. With proper time, attention, and training incorporating AI literacy best practices will come second nature if we are willing to learn and put in the effort. AI is clearly not halting it’s forward momentum anytime soon so we have to exercise our adaptability and expertise when in comes to how we move forward.
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The future of AI in higher education is not progressing according to any timelines, and so far, we are definitely in a reactive mode.
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What do you think is the future of AI in higher education? I personally think our future is exciting as we build physical ‘studios’ that embrace our traditional services and enhance a role of ‘Information stylist’ or ‘Personal AI Trainer’ – operating 24/7 with fully staffed lounges devoted to high end AI tools – all subscriptions paid (access & equity addressed) and staffed accordingly. Our collaborative spaces already have ‘Sensory Spaces’ & ‘Chill Out Zones’ with food vending options – so a one stop shop to collaborate and interact with both human and AI forces – I’m excited 😉
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AI is increasingly important for higher education and will continue to impact how students learn, research, and find information. AI can speed up and personalize the process of finding and summarizing content, and assist students and researchers in locating useful resources. While AI has great promise for education, the challenges of AI (e.g., bias, misinformation, and academic integrity) are also present. As an academic librarian, the role will not simply be to help someone find information, but to show how to responsibly and critically use AI tools.
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What do you think is the future of AI in higher education?
The future of AI is good and very transformative given that the state of technology development is advanced and this calls upon the librarian and libraries to continue guiding the students on new learning innovations in AI bringing new forms of inquiry and promote academic integrity. -
I believe AI will transform libraries and what we do as librarians. something for us to watch and learn.
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As academic librarians, we still much to learn about AI: How to use it with library management systems & databases; how to teach it as part of information literacy to students; and how to master what AI can/cannot do. This micro-course touched on the many opportunities, pros/cons, and challenges librarians are facing with AI across multiple disciplines.
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I believe the future of AI in higher education will be transformative, not replacing human expertise, but enhancing it. AI can support personalized learning, streamline administrative and research tasks, and help students and faculty access and analyze information more efficiently.
Libraries have a central role here: by promoting AI literacy, we can ensure that students and staff use these tools responsibly and critically, while we continue to guide, curate, and interpret information. In essence, AI is a powerful assistant for education—but human judgment, ethical oversight, and critical thinking remain irreplaceable.
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I think the future of AI in higher education will be its openness to use in everyday life. I don’t mean copying and pasting an assignment question and letting AI solve it—especially since, as we’ve read, it doesn’t always do well with certain subjects like math. Instead, I see AI as a tool that grows as it learns.
A good example comes from the movie Ron’s Gone Wrong, where students have B-bots that reflect their likes, dislikes, and even parts of their personalities. While the real future won’t look exactly like the movie, the point is that AI could move beyond phones, laptops, or PCs. We may see new ways for students to engage with each other—and for faculty and staff to connect too.
Right now, we often rely on email or Zoom, and sometimes we just repeat what’s in the textbook without digging deeper. Maybe AI will push us to pause and ask: Wait, what did I just hear? How can I relate this topic to something bigger?
In history, for example, we usually learn from the perspective of the victors. With AI, perhaps we’ll be able to explore more voices, more contexts, and new perspectives we hadn’t considered before.
This is just one small example of how AI could shape higher education. Now I’ll leave a question for you: What do you think AI will look like outside of school?
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This course highlighted how AI is transforming academic libraries. I learned that librarians’ roles now focus on guiding critical thinking, question design, and creative use of AI, moving beyond access to knowledge. Key takeaways include AI fluency, agentic AI applications, and the development of “imagination labs” to foster innovative, interdisciplinary research.
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I found the course content to be interesting, especially the articles. There are a lot of new things happening with AI.
Something to look out for is artificial intelligence browsers like Comet from Perplexity AI. AI is going to be integrated with everything in computers soon. https://www.perplexity.ai/comet So far after using it, I have found it to be better than all the browsers I have seen out there.
It will become necessary to learn a lot more about artificial intelligence just to hold a job. This will not be easy for many people. I find it to be a challenging both good and bad.
Every day, I read more about AI and try and read more books about it. We are at the beginning. A lot more is going to be written about it. Also a lot more is going to be absorbed into AI. We are entering the Zettabyte era on the internet which is far larger than any library. https://en.wikipedia.org/wiki/Zettabyte_Era Libraries are usually measured in Terabytes. In terms of information and artificial intelligence we are at the surface level of the ocean.
Take me to the Table of Contents.
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