2026 the 10 educational topics of the educause focus on how technical and data leaders in higher education develop collective will and support individual capacities. These two closely linked actions will help the institutions to flourish in the coming year。
Educause recently published the 10 major educational topics of 2026. These topics focus on the human dimension, demonstrating the focus of higher education technical leaders over the coming year. The challenges facing higher education are profoundly human. The guiding light for the technical community of higher education is not a front-line technology such as artificial intelligence (ai), but rather a connection. In addition to continuing to promote technological and data development, universities should bring together a wide range of different people and decentralized sectors to find common goals and to reach a consensus on what is most important and how best to move forward。
To this end, technical leaders in higher education are establishing contact within the school in two distinct ways: the development of collective will throughout the institution and support for individual abilities. On the one hand, it brings together all people and draws strength from shared values and commitments; on the other hand, it enables senior school leaders, staff, teachers and students to fully develop their individual talents and thrive in their work and learning。
2026 educause 10 education topics
1. Collaborative cybersecurity (collaborative cybersecurity): to build a culture of shared responsibility, enhanced end-user awareness, enhanced training and improved security services and support for accessibility。
The human edge of ai: empowering students and teaching staff to use artificial intelligence tools in a critical, creative and safe manner。
3. Operational and financial decision-makingData analysis(data analytics for operatio)Nal and financial insights: use data analysis to see expenditure patterns, enrolment trends and identify areas where cost savings and operational efficiencies can be achieved。
Building a data-cultural cultures the institute: expand and improve access to data to fully unlock the full potential of data as a strategic asset。
5. Knowledge management for safer artificial intelligence (knowledge management for safer ai): risk reduction of artificial intelligence by integrating knowledge management into data governance, privacy and ethics projects。
6. Prudent application of new technologies (measured approaches to new technologies): better technology investment decisions, or opt for non-investment, through clear cost, return on investment (roi) and legacy system assessments。
7. Technical literacy for the future workforce: supporting technical training and education in specific disciplines to help students acquire the technical skills required by the market, thereby increasing their success rate。
8. From passive to active: use of data for scenario modelling, prediction and prediction to enhance school agility and planning capacity。
9. Artificial intelligence driven efficiency and growth (ai-enabled services and growth): using artificial intelligence, robotic process automation and other analytical capabilities to reduce operating costs, simplify processes and improve strategic and operational decision-making。
10. Policymakers ' data skills and literacy (design-maker data skills and literacy): increase the value of school data by training policymakers to use and interpret data correctly。
Collective will
In 2026, technical leaders will focus on building collective will within their schools, helping to establish common values, standards and goals that will enable schools to move forward in an agile and coordinated manner。
Building collective will is a difficult task in an area that has traditionally been slow to adapt to the informationization of higher education and where many functions are fragmented. Many school leaders and practitioners feel deeply trapped in maze-like decision-making structures, which are becoming less and less adapted to an increasingly rapid and unpredictable world。
“historyly, it may take several years for universities to change their professional and course curricula, through a hierarchy of committee approvals and complex processes.” jan hesthaven, director of karlsruhe institute of technology, germany, explained that “in the current rapid technological development, several years are almost eternal. Two years later, when we introduced the new professional set-up, it was probably completely out of date.”
Those “committees and cumbersome processes” that slow the pace of decision-making are not manifestations of collective will, but rather of a lack of collective will. Shared governance, as a common expression of collective will, clarifies the criteria, roles and processes for decision-making, thus making decision-making faster than slower。
As john lutz, vice-chancellor of the university of vanderburg, stated: “in universities, barriers to information between sectors are widespread.” barriers exist in terms of data, technology deployment, and even strategic planning and decision-making in higher education. When institutions are fragmented and have different perceptions of systems and realities, it will be difficult to reach consensus on complex decisions affecting the entire school community. Schools with a collective will need to break down these barriers by integrating resources and knowledge within the campus and developing a school-wide perspective. “the university of vanderburg has made great progress on this issue over the past few years, creating a flexible and agile approach to inter-college and cross-sectoral collaboration.” john lutz indicated。
In the coming year, technical leaders will help schools become more agile and reduce barriers by supporting coordination and collaboration based on data and artificial intelligence. This requires the sharing of reliable data and insights across the school, encouraging the active participation of school-wide teachers and students in relevant practices, and developing centralized policies and standards around the use of data and technology. Technical leaders should also engage a wide range of campus stakeholders to ensure that the collective will of schools draws on the wealth of knowledge and professional insights of individual members。
The efforts of the technical leaders to nurture the collective will of the school will focus on the following five areas:
Data analysis for operational and financial decision-making: use of data analysis to provide insight into expenditure patterns, enrolment trends and to identify areas for cost savings and operational efficiency (topic 3)
Building a school-wide data-centred culture: expanding and improving access to data and fully unleashing the full potential of data as a strategic asset (topic 4)
Knowledge management for safer artificial intelligence: reducing the risk of artificial intelligence by integrating knowledge management into data governance, privacy and ethics projects (topic 5)
Prudent application of new technologies: better decision-making on investment in technology or opting for non-investment through clear cost, return on investment (roi) and legacy systems assessment (topic 6)
From passive to active: using data for scenario modelling, prediction and estimation to enhance school agility and planning capacity (topic 8)。
Each of these topics presents a unique set of challenges to schools and carries unique benefits. But they have one thing in common: to bring together people within the school. When this happens, teams and individuals can build closer links, share resources and agree on key decisions。
Personal competence
In 2026, the technical leaders will support the ability of each individual to use school technology and data effectively, safely and creatively to regenerate them。
Individual capabilities are a concrete expression of collective ideals. For example, the innovative use of artificial intelligence technologies in the classroom has a transformative impact precisely because they are integrated into school strategies and support systems, enabling individuals to adopt and apply them. School norms and guidelines, built around the adoption and use of technology, will strengthen students ' capacities as technology users and industry innovators rather than limit them。
Christopher buddle, deputy dean of teaching and academic planning, mcgill university, described how artificial intelligence was seen in his school as an enabling teaching tool. “many people see artificial intelligence as a threat to school and academic integrity, rather than as a means to improve teaching methods, to improve evaluation and to bring benefits to students and teachers”, he explained, “we are working with the it sector and with technologists to truly find ways to use technological wisdom to do things, rather than simply seeing it as a clumsy tool”
In the coming year, the technical leadership will empower all members of the school to achieve the “net gains” from the technology and data that carry the collective will of the school. This requires technical leaders to be good at educating and training users so that they can safely and effectively adopt artificial intelligence and other technologies, and to promote cooperation with project and academic leaders to ensure that students receive the required training. This requires technology leaders to be close to and connect with individual technology and data users, to listen to their expectations and setbacks and to develop resources and support accordingly。
The efforts of the technical leaders to support individual competencies will focus on five areas:
Collaborative cybersecurity: building a shared responsibility, raising end-user awareness, enhancing training and improving security services and supporting access to a culture of cybersecurity (topic 1)
Human advantages of artificial intelligence: empowering students and teaching staff to use artificial intelligence tools in a critical, creative and safe manner (topic 2)
Technical literacy of the future labour force: support for technical training and education in specific disciplines to help students acquire the technical skills required by the market, thereby increasing their success rate (topic 7)
Efficiency and growth driven by artificial intelligence: use of artificial intelligence, robotic process automation and other analytical capabilities to reduce operating costs, simplify processes and improve strategic and operational decision-making (topic 9)
Data skills and literacy for decision makers: increase the value of school data by training policymakers to use and interpret data correctly (topic 10)。
These five topics cover a wide range of areas of individual application: student curricula, administration, strategic planning, security awareness, use of artificial intelligence, interpretation of data and many other applications. The common thread behind these topics is that individuals play a central role in translating the collective will of institutions into reality. In sum, they recognize that the soul of the school is expressed through the voices of every human being — voices that are dynamic, sparkling ideas and empowered to change the world。
In sum, strengthening the collective will of the school and empowering its members to flourish and succeed in their work and learning will be a central theme for the technical leaders of the coming year and the key to enabling the school to chart the way forward in the changing field of higher education。
