Institutional resilience in difficult times

Is Higher Education in crisis?

Over the years, we have grown used to hearing that higher education is in crisis. There have been disruptive events like the Great Recession (budget cuts, recruitment freezes, declining student completions) or the pandemic (the switch to online learning, research disruption, mental health issues), as well as unwelcome phenomena like the “Postdoc Exodus” (postdoctoral researchers leaving academia for industry), or “Publish or Perish” (the pressure on academics to publish to advance their careers and secure funding). While many of these challenges persist, universities have proved resilient, and most of the commentators’ gloomier projections have not yet come to pass. For this reason, now that much of academia is reported to be “in crisis” once again, it is tempting to be sceptical. Having to manage with limited resources is problematic but certainly not new, while many careers in academia have always been precarious, especially those of junior researchers. Perhaps it has been bad for so long we’ve forgotten what good looks like?  

However, there is arguably something different about the problems now facing the sector – and not just their volume. One of the most serious issues is the widespread decline in government funding for higher education, either because of government cuts or policy changes that have the same net effect. The US government has frozen federal research grants, which account for between 10 and 50 percent of the operating budgets of American universities, while Universities UK says that the country will experience an estimated £1.4 billion net reduction in funding for higher education providers in England for the 2025-26 academic year. Meanwhile, countries like Japan have seen stagnation, with a 1 percent annual fall in government funding since 2004, and even in China, a slowing economy may lead to less public investment in higher education. Such shortfalls become even more significant when viewed in the context of declining student enrollments. While these may be connected to waning faith in the relevance of higher education or falling birth rates, the situation is exacerbated by the desire of governments in countries like the US, Canada, the UK, and Australia to either cap or tax their international students.   

Systemic financial pressures, a shift in the perceived value of university degrees and academic work, and other factors like changing expectations around technology, all point to more fundamental issues related to the structure and purpose of higher education itself. Of course, many of these problems have been present for some time, with factors like the ready availability of lucrative overseas students helping to “paper over the cracks” in some countries, but the current global economic and political climate has given them a new urgency. There is a disturbance in the consensus around the state’s role in supporting, or securing access to, higher education, as well as the societal benefits this is thought to bring (for a fuller discussion, see the recent Not Alone podcast on the future of higher education). While universities continue to play a major role in society – creating a skilled workforce, driving social mobility, developing research that supports economic growth and better health outcomes – this message no longer seems to be landing with either governments or the public.

Coordinated solutions for institutional resilience

While many of these problems can be attributed to social, political, and economic factors that are largely beyond academia’s control, doing nothing is clearly not an option. But how should universities respond? Although there are plenty of recommendations around diversifying income streams, strengthening student support systems, and engaging in strategic partnerships, the fundamental nature of the challenges facing universities suggests that a more comprehensive approach is required. While national government interventions would be welcomed by some, the appetite for the kind of financial commitment this might involve is usually low, with growing concerns in some countries around the need to protect the independence of academia. How can higher education institutions formulate their own joined-up approach? 

Practices differ from institution to institution, but on the practical level there are often surprisingly few holistic programs. While the twenty-first century has seen a growing number of universities adopting strategic 10-year plans – usually aspirational roadmaps that take in areas like funding, research impact, digital innovation, community integration, and diversity, equality, and inclusion (DEI) goals – these are often very broad-based and can suffer from a lack of focus or an excessive number of moving parts. Moreover, reporting on the overall success of such complex initiatives has sometimes proved challenging. Meanwhile, University leaders, Research Officers, Heads of Department, Librarians, and Faculty all have their own professional objectives that benefit the wider institution in their various ways, but with very little connective tissue between them, despite frequently overlapping concerns like student outcomes. One unifying initiative shared by a growing number of institutions is a commitment to digital transformation.  

The scope of digital transformation

Definitions of digital transformation vary, but one of the best academia-oriented explanations comes from an Educase Review blog post:

(Digital Transformation) is a series of deep and coordinated culture, workforce, and technology shifts that enable new educational and operating models and transform an institution’s business model, strategic directions, and value proposition.

As that post makes clear, digital transformation “can make institutions more resilient, flexible, and relevant as they face an array of increasingly difficult challenges.” More specifically, this can mean more personalized learning experiences for students, with improved access to information and resources, heightened engagement, and better workplace readiness. For staff in the Research Office or the Library, digital transformation might drive enhanced operational efficiency through the automation of processes, freeing up time to focus on more strategic or human-centered work. In the meantime, for Provosts and Pro-Vice Chancellors, such a program can facilitate more data-driven decision-making around resource allocation or research and funding priorities. The underlying theme here is that while digital transformation starts with technology, it emphatically does not end there. The digital estate – the combined digital assets of an institution –  is only the means of transformation, the mechanism for enabling wider business and operational change across the university. 

Like other departments, the IT teams that typically lead digital transformation programs in universities often struggle with limited resources. Staff are frequently charged with managing IT environments that have grown in a piecemeal way over time, creating a disjointed user experience, growing costs, and increasing the number of potential entry points for cyber-attacks. The challenge is to optimize this ecosystem so that it can enable wider institutional priorities. Taking the example of cybersecurity, while technological solutions are required, an effective strategy must include “human” considerations such as governance, education, training, and awareness programs. To quote Educase again, “Institutional (Digital Transformation) initiatives can succeed only through the strategic application of a changing set of technologies in support of new institutional directions.” Such an approach, successfully executed at the institutional level, can help the university to become more efficient and flexible, driving better business outcomes and delivering more value to its employees and stakeholders. It might indeed provide much-needed support for key areas like funding acquisition and management, or teaching and learning, but it remains highly ambitious.  

How should we understand the scope and promise of this ambition? It is a long journey from simply digitizing information to a broad-based strategy that can potentially support university resilience during turbulent times. How did we get here?

The story so far…

Digital transformation began in the corporate sector in the mid-1990s with the growth of the internet. Initially, the focus was indeed on digitizing information, usually from analog or print sources, with an emphasis on organizing, archiving, and retrieval (see the excellent diagram from the Educause Review).  By the early 2000s, automation had become a dominant theme, with many companies moving towards process-oriented digitalization. However, the virtual environment was now expanding rapidly with the development of cloud hosting, mobile technologies and advanced data analytics.  

By this time, digital transformation was also prevalent in the public sector as governments sought to integrate advanced technologies to streamline their services, address societal challenges, and boost economic productivity. Digital strategies like the ones developed by the US and UK governments in the early 2010s became increasingly ambitious, particularly in Australasia, where Japan’s Society 5.0 (2015) was followed by South Korea’s Digital New Deal (2020) and Australia’s National Digital Economy Strategy (2021). Most of these initiatives – mindful of the needs of the future workforce – contain some kind of digital education policy. While these programs often incentivize technological upgrades by streamlining procurement processes or by offering some targeted funding, there is a limit to how far national governments can drive change at the institutional level, especially in non-state-backed education systems.  

While Higher Education is usually thought to have followed the corporate sector in its adoption of digital transformation, it led the way in some areas, such as the widespread adoption of online journals from the mid-1990s. This interest intensified over the following decades as leaders began to focus on areas like operational efficiency, seeking to position their institutions for long-term success by streamlining processes, saving money, and delivering more internal and societal value. The pace of change increased, first in Asia in the wake of the SARS pandemic of the early 2000s, then globally from 2020 as the COVID-19 pandemic took hold. Universities invested quickly and often heavily in tools and technologies to facilitate remote learning, research, and mental health support – sometimes creating a tangled legacy that IT teams are still grappling with today. The interest in and momentum behind digital transformation also grew as a result of organizations like JISC in the UK developing frameworks and toolkits to support institutional efforts in this area. While there are no overarching surveys, case studies discussed in the scholarly literature, or undertaken by organizations like JISC or QS, indicate that these programs often met with some success, with underperformance generally being linked to the neglect of areas like change management or the cultural dimension. 

Then, towards the end of 2022, a San Francisco-based tech company provided a “research preview” to tease a refreshed version of a two-year-old technology, with limited fanfare and low expectations. The technology in question was OpenAI’s ChatGPT, and it was about to reframe the whole discussion of technology on campus. 

AI – Phoenix or Cuckoo?

It is still difficult to gauge the impact of AI across higher education, with the speed of adoption varying significantly both across and within institutions. For some university leaders, AI is potentially a phoenix, the bird associated (in Western mythology) with renewal and rebirth, helping to regenerate the sector in the face of the deep-seated problems discussed above. However, for others, AI is more of a cuckoo, some species of which famously lay their eggs in other birds' nests. In this narrative, AI is displacing existing digital transformation initiatives, disrupting centralized planning and commandeering resources that might be better employed elsewhere. More specifically, there are concerns that ad hoc AI adoption strategies will exacerbate already devolved IT environments, impact operational efficiency, and raise cybersecurity risks. This situation could be made worse by uncoordinated AI acquisitions across the university, feeding into the “shadow IT” problem – the use of systems, devices, software, or services that are not approved or managed by an institution’s IT department. 

To complicate matters further, some corporate commentators are suggesting that digital transformation has been superseded by “AI transformation,” with a digital-centric paradigm being replaced by an intelligence-centric one, pointing to the potential of newly mainstream agentic technologies to back up their claims.  Another, more sophisticated view is that digital transformation and AI transformation are two parallel but complementary processes that can even be benchmarked against one another. While both perspectives are articulated with conviction, the overall picture is one of confusion, with serious analysis jostling for position with a kind of buzzword-laden commentary that calls to mind another bird, the magpie, with its well-known fondness for collecting shiny new objects.

The right foundations

This is all highly theoretical, but university technology leaders are seeing the clash between these two “transformations” firsthand. Sometimes excluded from AI decision-making processes, they may be frustrated by the lack of an institutional framework to help handle fragmented governance, risks posed by misinformation and disinformation, and the intensified problem of skill gaps across campus. They worry about heightened exposure to evolving cybersecurity threats and threats to academic independence posed by Big Tech companies, increasingly active in the academic space (see the Inside Higher Ed 2025 Survey of Campus Chief Technology/ Information Officers for a US-based overview of these concerns). In the meantime, key areas like data quality, integration, and other emerging technologies, such as quantum computing, can be neglected. With the excitement around AI showing no sign of fading, a strategic organizational reset may be necessary. In the words of Chris van der Kaay, consultant and former-CIO, “AI has us not only thinking about how we’re doing things but why we’re doing them, which is why it’s important to have…enterprise-level thinking in using these tools” (Agency at Stake: The Tech Leadership Imperative).  

Where will this enterprise-level thinking come from? The fact is that if universities are going to rise to the challenges facing them, including effective AI implementations, they need to have the right foundations in place – quality data (curated, normalized, and FAIR), data strategy, the right technology, and the right expertise. These can be considered to be a part of a digital transformation process that is neither outmoded nor rivalled, but forms an important prerequisite for other programs and initiatives. 

The moving walkway

In fairness, the term “digital transformation” invites some criticism because it implies a simplistic transition to a better state. Given the rapid pace of change in higher education and beyond, we should probably be cautious around the concept of “digital maturity,” although this does not mean that step-by-step models like those developed by not-for-profits Educause in the US and JISC in the UK are not helpful. Still, even if you manage to attain what seemed to be technological readiness when your program commenced three years ago, the chances are that the new systems and tools that arrived in the interim – not to mention changes in the institutional, political, and economic landscape – will mean you remain as far from your objective as ever.  

In summary, transformation is not a simple one-way ticket to nirvana. In fact, McKinsey points to a 70% failure rate among transformations, citing “insufficiently high aspirations, a lack of engagement within the organization, and insufficient investment” as the main reasons. While these points are well made, it makes far more sense to see the process as open-ended – or as the authors of a JISC paper memorably put it, “digital transformation is a commitment rather than a destination.”  Put another way,  the quest for digital transformation is like heading the wrong way on a moving walkway – it is possible to work towards a state of excellence, but if you don’t want to lose ground, you have no choice but to keep going. 

Digital transformation in academia – key areas 

If digital transformation is indeed a commitment, what are you committing to? While points of emphasis will vary by institution, below is a simplified overview of some of the key elements of an academic digital transformation. 

Core components 

• Digital Infrastructure and Operations – Includes the institution’s hardware, software, networks, security architecture, and data centers.  

• People and Culture – Enables areas like recruitment, faculty management, diversity and inclusion, and student support programs. Also covers training to develop the digital capabilities of staff and students – for example, information and AI literacy programs – as well as the related legal and ethical governance frameworks covering intellectual property, research integrity, and effective tool and information use. The shared beliefs and behaviors fostered by these systems, initiatives, and guidelines comprise the digital culture of the institution.  

Use cases 

• Knowledge Creation – Creation of knowledge through the research process (search, literature review, data collection, etc.) and research outputs (articles, pre-prints, book chapters, etc.). Involves support for researchers at all career stages through investment in and access to relevant tools, systems, and technologies. 

• Knowledge Dissemination – Focuses on tracking the impact of institutional research outputs across the research community and society as a whole via indicators such as citations, altmetrics, patents, policy citations, or inclusion in systematic reviews. Also covers the ways in which a university showcases its research and research impact to the world via public-facing portals, institutional repositories, conferences, publications, etc. 

• Knowledge Development – Focuses on how digital approaches can enhance teaching and learning processes to improve student outcomes. This includes access to relevant information and tools, personalized learning experiences, virtual classrooms, collaborative learning tools, support for assessment, and improvements to the efficiency of educators.  

• Knowledge Management – Covers effective data analysis and management to support decision-making in areas like research strategy, collaboration, funding, and recruitment.  

Delivering on the promise of digital transformation 

Across much of the world, universities face a series of fundamental challenges. Behind the urgent problems around funding, student enrollments, and the integration of new technologies, there are deeper questions relating to the perceived value of academic knowledge and the role of higher education in society. In a sometimes volatile political climate, universities can be caught in the crossfire of political debates, facing accusations of bias or calls for censorship, while there is growing concern around ransomware attacks and state-sponsored cybersecurity incidents. 

What should universities do? Many institutions have cut costs – courses, staff, departments – while exploring more sustainable funding models, but both approaches risk sacrificing long-term goals to short-term expediency. Government interventions or large-scale corporate partnerships may have some benefits, but can also pose an unprecedented threat to academic integrity. 

While universities are implementing programs across the crisis areas, these activities can be disjointed, compromised by the disparate agendas of different departments and functions, or suffer from a lack of clear leadership backing. What is often missing is enterprise-level strategy, planning, and support – an authentically holistic approach that involves both top-down leadership and bottom-up participation. This is easier said than done of course, but best-in-class digital transformation can provide a ready-made model for this type of initiative – and is itself a key component of any institutional response to the current social and economic conditions. Perhaps even more than during the formative pandemic years, resilient universities must pursue sustainable coordination across their data, technology and people.