Universities after digital transformation: four plausible futures
Will students learn to save the planet – or just optimize their AI scores? Bonus: choose your future syllabus.
Hello, this is Six Impossible Futures, a newsletter that helps you develop a critical perspective on what’s possible. This is the second issue of Alternative Arcs, a series unpacking futures research. In each issue, I break down peer-reviewed studies into thought-provoking explorations and put them into context to spark your curiosity about possible futures.
Universities are entities so big and complex, that almost no major trend passes without affecting them. In the last years, universities have faced what once were ‘unthinkable’ challenges. The Covid-19 upended traditional on-campus teaching. The rise of micro-credentials challenged the monopoly of degree programs. Then AI burst onto the scene, with almost all students (92%) now using it in some form, and generally not considering it cheating. Right now, governments and political leaders are tightening regulations. The policies of the Trump administration send ripple effects across global higher education, from research funding to international admissions. (The day after the U.S. election, Study.eu reported a threefold spike in visits from U.S.-based users.)
Some forces shaping universities’ futures are more tangible and pressing, one of them — digitalization. In the European University Association survey of leaders from almost 500 universities, 84% said that digitalization has the highest impact on their strategy. (Followed by the disruptions of Covid-19 at 76%, and the rise of cross-institutional cooperation — 68%). Similarly, OECD’s report names “rapid advancements in technology, including AI” a key megatrend for futures of education, together with ecological crisis and deepening societal challenges of inequality, fragmentation, and polarization.
Digitalization stands out as both a disruptor and a bridge to new possibilities. This transformation raises a key question:
What might higher education and research look like in a world increasingly dependent on digital resources?
INRAE and Agreenium, two French public institutions specializing in food, agriculture, and environmental science, have explored this very question. In the article Exploring Digital Transformation in Higher Education and Research via Scenarios (Barzman et al. 2021), they map out four plausible futures for universities1 after digital transformation.
I chose this study for Alternative Arcs because it’s close to my heart as a recent graduate, and it also offers a glimpse into how our kids might experience university education.
Besides, it raises questions important for our society as a whole: should universities prioritize technology-driven efficiency or human-centered learning? How much influence should the public sector, private industry, and civil society wield? As the research team notes, the impact of digitalization in academia reverberates across scientific disciplines, economic sectors, and civil society, creating complex interdependencies and non-linear changes. Let’s explore this territory.
A peek at the methodology
Unlike the critical uncertainties approach we saw in the previous Alternative Arcs issue, Barzman et al. employed morphological analysis to build their scenarios. Scenarios draw on input from more than 50 university-affiliated experts in innovation studies, foresight, economics, educational sciences, HR management, IT, data management, AI, and teaching and research in agro-food-environment studies (given the institutions behind the study).
The first step was to identify drivers of digital transformation in universities. Roughly 30 drivers were described and grouped into seven larger themes, such as the practice of research, or university-society interaction. Next, the researchers did an extensive horizon scanning to study past and current trends and potential disruptions related to each driver.
From here, for each of the seven themes, the team developed three to four alternative hypotheses describing what its state might look like in 2040. These alternative states were then combined into four scenarios, each plausible, coherent, and with strong contrast from each other. Lastly, the team performed a SWOT analysis for every scenario, evaluating the strategic position of a university within each future.
Scenarios
Let’s look into the alternative futures of universities in 2040. (Please note the strong EU-context in some scenarios, as the study was made by French institutions to inform their strategy in the first place.) To bring these scenarios into sharper focus, I’ve expanded the descriptions from the study with small vignettes and recent signals that point to how these futures are already beginning to unfold.
Now imagine you're choosing a university course — but it’s the year 2040. Depending on which future unfolds the courses available, and the very structure of university teaching and research look remarkably different.
Scenario 1: Universities in the shadow of digital giants
Ping! A soft chime blinks across your learning dashboard: new course now available for enrollment.
AI-Integrated Research Project Management
This self-directed course prepares students with the skills needed to manage research projects in a digital-first academic ecosystem. Practical assignments will include real-time simulations using platforms and databases from the corporate partner. Students will also learn to optimize project proposals for algorithmic funding evaluations. Successful participants earn a transferable digital badge in AI-driven project coordination, automatically added to their credentials portfolio (a baseline requirement for entry-level research positions).
In this scenario, tech giants have become dominant players in research and education. They build campuses’ digital infrastructure, develop centralized research platforms, and provide computational power to universities — in exchange for taking ownership of research and teaching data. In research, AI-driven platforms serve as central hubs for the distribution of research grants and matching projects with suitable research teams.
Education is available through private and public institutions, as well as degrees offered in partnership. Private providers dominate high-demand, niche subjects (think areas like synthetic biology, AI governance, and quantum logistics), while public institutions focus on broader, less commercially attractive offerings. A unified learning management system tracks the life-learner’s journey across institutions. Assessment is handled through digital badges, that signal skills to employers.
Teachers have become freelancers whose digital reputation is now measured Uber-style based on student ratings and engagement metrics; researchers transition to the private sector, where their work is evaluated with AI scoring, that factors in publication output, project scale, and funding secured.
In a nutshell, in this scenario research and education have become faster, digitized, and more interconnected — but also more precarious, market-driven, and unevenly distributed. Seems like many seeds of this future are sown. Take AI-powered platforms for teaching and learning: Xi'an Jiaotong-Liverpool University in Suzhou, Jiangsu province of China, has introduced the XIPU AI system to assist educators in course design and analysis of student progress through data and provide students with customized learning and review support.
Private-public collaboration between universities and tech firms expands. At The University of Hong Kong, Huawei is building a next-generation smart campus powered by Wi-Fi 7 and a 10 Gbps network, with plans to deploy a smart campus IoT. La Trobe University in Melbourne has partnered with Microsoft to implement an “AI-first” operational model. One of their pilots is a digital assistant “Troby” that reduces time spent on manual research and retrieval of academic articles.
Meanwhile, we’re also witnessing the rise of micro-credentials and corporate-backed education. Among advocates for hands-on and self-directed is Elon Musk, now leading an overhaul of U.S. higher education. He frequently notes that many of his top employees have no formal college degrees.
Despite numerous hints of this future in the present, we should not forget that futures don’t unfold in just one direction. Another scenario is plausible — let’s take a look.
Scenario 2: Universities and digital tech for the planet
A new course just launched in a shared European digital course catalog:
Acoustic Restoration of Nature in the Local Context
This transdisciplinary course explores how the sounds of healthy ecosystems can be deployed to attract wildlife back to damaged habitats. Professors from sustainability studies, sound engineering, and behavioral biology lead the course, providing students with a well-rounded perspective on acoustic restoration. The course includes group projects for students to collaborate on regional ecosystem challenges with peers from the same geographic areas and prototype acoustic restoration strategies for local contexts. Note: this is a fully online course, with lectures 3 and 5 in Italian (live AI translation available).
In this scenario, the environmental emergency has become the top priority for policy and research. Universities have evolved into hubs of environmental stewardship to meet the pressing demands of climate change, food security, and sustainable resource use. Curricula and research agendas serve the common good, supported by national and European investment. Trust in science has been carefully rebuilt. Universities leverage digital tools to elevate the status of teaching and research professionals and promote critical digital literacy among staff, students, and the general public.
Researchers are mainly employed by governments and their work follows the “One Health” approach, connecting human health and ecosystem health. They work on addressing planetary-scale issues through interdisciplinary collaboration and contribute to shared, global databases to allow an easier flow of knowledge across institutions, disciplines, and borders.
Higher education has become international and interconnected. Courses are interdisciplinary and structured around real-world challenges. English has become a default language, plus real-time AI translation is available between any language to enable broad knowledge access. Student mobility allows learners to build customized pathways through a shared European digital course catalog. Degrees are seamlessly recognized across the EU and emphasize the application of thematic disciplinary knowledge to region-specific problems.
The result is an academic landscape that is relevant both globally and locally. As for the seeds of this scenario, today’s academic landscape already contains many of its elements: international research networks and infrastructures, widespread use of English, and areas of research relevant to global challenges. What’s missing, the authors note, is a systematic collective effort to leverage these assets to address planetary issues.
I found one compelling signal of such an effort: six European universities are co-designing a transnational Master’s program in Planetary Health. Its focus will be on the skills and knowledge needed to address global challenges and tackle the complex links between planetary and human wellbeing. It will be open to students from any discipline background and have mechanisms like joint admission and integrated teaching across six partner universities. (Feels like a setup lifted straight from the scenario!)
There are also one-off research programs in universities, such as Earth-Nature-Society in the Goethe University Frankfurt’s Center for Critical Computational Studies, that leverages computational and data-based methods to navigate planetary polycrisis. Their teaching offerings include modules on critical computational literacy, that educate to engage with digital tools from a socially and environmentally informed perspective. Across the Atlantic, UC Davis holds a Grand Challenges initiative for interdisciplinary collaboration on complex global problems.
(And if you're curious about acoustic restoration of nature, this is a real emerging area of research you can explore here.)
Two more alternative futures to explore. Moving on.
Scenario 3: Digital territoire-based university ecosystems
Imagine this on your syllabus in 2040:
Citizen Science and Public Decision-Making in Food Systems
In this course, students will dive into participatory research practices, working with local communities, farmers, and scientists to co-create knowledge on agroecological practices. Through six-week field-based projects, students will collect data and engage directly with grassroots networks and stakeholders. The course will challenge students to think critically about how local knowledge can be integrated with scientific research. By the end of the course, students will be ready to contribute to shaping resilient, community-driven food systems.
In this scenario, universities have evolved into territoire-based2 hubs, deeply embedded within their local systems. They blend higher education, innovation, and community engagement to produce place-based, hyperlocal knowledge, responding directly to the needs of surrounding communities.
The research agenda is shaped by the dialogue with local stakeholders. Participatory science plays a central role, blurring the boundaries between professional researchers and informed citizens. A new culture of complementary expertise has emerged, grounded in both scientific knowledge and lived experience. Digital platforms and open labs create bridges between researchers, communities, and local businesses, while AI helps process data from sensor-rich environments.
In education, teachers are employed by local governments and serve as guides, helping students navigate opportunities for both digital learning and hands-on local involvement. Emphasis is placed on applied learning within the community. The result is a decentralized model of knowledge-making, that is flexible, participatory, and rooted in local realities.
The seeds of this future can be found, for example, in numerous participatory science projects gaining momentum in the last 5 years. One example is the Cyanobacteria Monitoring Collaborative program in the U.S. which tracks harmful algae blooms. Photos and data submitted by citizens through an app contribute to understanding regional patterns, such as when and where blooms occur.
Community-driven research agendas are also gaining traction. The Coalition of Urban and Metropolitan Universities promotes hyperlocal research collaborations between universities and communities across the U.S. and Canada. At the Royal Melbourne Institute of Technology, the PlaceLab initiative invites local residents and organizations to co-design bite-sized, hyperlocal research projects with immediate application and impact.
We also see examples of how digital research infrastructure can serve local needs. The University of Oregon’s Hazards Lab uses NVIDIA Jetson-powered edge computing to monitor wildfires through the ALERTWildfire system and deliver real-time data to residents, firefighters, and municipalities.
Scenario 4: Universities face digital frugality
As we turn the page to the last scenario, another course catches your eye:
Learning and Teaching in a Post-Digital Overload Era
This course explores the changing dynamics of education in a digital frugality world. Students will study emerging pedagogical models built around minimal tech. Through hands-on experiments, they will design and test educational strategies that prioritize in-person engagement, cognitive clarity, and locally co-developed content. By the end of the course, students will understand the implications of digital frugality in education and learn to develop resource-conscious teaching.
In this scenario, digital transformation in the 2020s reached a breaking point, driven by resource shortages, high energy costs, and growing environmental and psychosocial harms. In response, the EU implemented regulations on digital practices. The most important is the data-byte tax that limits data usage, storage and computational space for individuals and organizations (although additional data-byte rights can be purchased from the European Central Digital Bank). The culture of digital frugality has slowly emerged, where people embraced more intentional digital habits to reduce cognitive overload, multitasking, and tech-driven burnout.
Both research and teaching became decentralized and closely aligned with local needs, using fieldwork and hands-on collaboration to co-create knowledge. Research priorities pivoted toward supporting frugal digital practices to reduce environmental and social impacts. In practice, researchers optimize, pool, and share resources. They collaborate in hybrid, interdisciplinary networks to share tasks and knowledge. One common requirement is to conduct cost-benefit analyses before projects requiring significant digital resources.
Education emphasizes field-based learning, community engagement, and the use of hybrid formats. Teachers become facilitators embedded in local learning ecosystems, guiding students in learning and developing frugal digital habits.
This future takes a sharp turn away from today’s digital acceleration — an unexpected shift, but not an implausible one. Some cracks are appearing in the digitalization trend, signaling a possibility of a crisis (a tipping point for this scenario). Among them are rising energy and resource pressures. In many places, AI-driven energy demand is outpacing the expansion of the grid. In central Ohio, for instance, power lines will hit full transmission capacity in three years, even as three New York Cities’ worth of data centers wait to connect to the grid after 2028. Beyond electricity, a great amount of water is needed to cool the hardware, which threatens local ecosystems and biodiversity.
Demand for critical minerals such as lithium and cobalt is projected to soar by 500% by 2050, fuelling potential shortages and possibly deepening environmental and social issues associated with mining in the Global South.
The psychological side of digitalization is becoming harder to ignore, too, as we struggle with the pressure to optimize and accelerate life via digital tools (this is a superb essay on the topic by
).Some novel low-impact infrastructures like network-based biocomputation, that may be useful in this future, are in the early stages of development. As for signals from universities, they seem absorbed in keeping up with the current digitalization wave, not pausing to consider a future of digital frugality. (And really, who among us is preparing for that?)
Critical cross-cutting questions
From these contrasting future scenarios, a cascade of critical questions emerge. They don’t necessarily demand immediate answers, but they do surface the values, assumptions, and priorities shaping our imaginaries of higher education and research.
First, the question of research agenda-setting: who and how will influence it? Should the public good be prioritized over economic competitiveness? What is the right balance between global priorities and local (or even hyperlocal) needs? And across all this, how can universities keep academic freedom while navigating complex stakeholder landscapes that include governments, industries, and local communities?
Second, as digital tools become more prevalent in education — in all scenarios but the fourth — how do we ensure equitable access to them in different social, economic, and geographic contexts? What should happen to student data? Who is responsible for the digital literacy skills of future students and educators? What are the potential long-term implications for teaching and learning methodologies in different scenarios? What about biases in AI-driven tools? (Like, if I get tailored learning paths, can I be 100% sure that the algorithm doesn’t factor in my gender, ethnicity, or other things that shouldn’t matter but often do?)
Then, there’s the shifting role of university staff. Across scenarios, we see a spectrum from precarity to public leadership, from freelancers to civil servants. Which model is more desirable? How might recognition and compensation change depending on whether educators are seen as just ‘digital guides’ or local changemakers?
And finally, as several scenarios highlight collaboration across institutions and borders, several broader questions come into focus. Will such partnerships genuinely support equitable participation between the Global North and South? Is increased mobility of researchers and students a form of brain circulation — or a mechanism of brain drain? What happens when English becomes the default language of higher education? (Finland’s current debates over English-language programs offer a glimpse of tensions.)
These questions may not yield easy answers, but they’re essential if we want to actively shape futures, not passively observe how they unfold. Universities are places of research and innovation, education, community service, and social change. Their futures are intertwined with the future of us all.
The original study uses the term higher education and research (HER)
The researchers use the French term terriroire which refers to a geographical area that includes the human communities providing its economic, ecological, and cultural reality.