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The rapid proliferation of AI tools is just one part of an ongoing era of global digital transformation. What actions can we take to create the digital future we want to see?

An era of global digital transformation

In the 2024 EDUCAUSE Horizon Report | Teaching and Learning Edition, a global panel of higher education experts identified the trends most likely to impact higher education over the next ten years. These trends span five distinct categories – social, technological, economic, environmental, and political. For the first time, the report also identifies AI-related trends across all five categories, looking at the ways AI is impacting all areas of life, learning, and work.

So, what are the impacts of AI on the way we communicate with each other, the tools and methods we use to teach, our students’ holistic educational experiences, our economy and workforce, climate change, and political processes?

Keeping up or risking obsolescence

Given the widespread impacts of AI for daily life and work, higher education leaders know they need to keep up with digital advancement or risk falling behind. In our recent study of the AI landscape in higher education, we found that the three biggest motivators for AI-related strategic planning were the rise of student use, risks of inappropriate uses, and concern about ‘falling behind’ in adoption. Further, for nearly half of university leaders AI is a strategic priority at their institution, and indeed a part of their responsibility to prepare students for life and work in a digital world.

Unsurprisingly, strategic interest in AI is not expected to slow down anytime soon. For example, in a recent poll of higher education professionals, they told us that they intend to increase their use of generative AI over the next two years in all of the following areas: enhancing student experiences, creating new approaches to learning design and assessment, boosting productivity by automating administrative processes, creating new curricular programmes, and creating new core capabilities.

AI throughout the higher education institution

AI is already impacting many core functions and activities of higher education institutions, at least to some extent. Indeed, our research finds that institutional policies on teaching and learning, technology, cybersecurity and data privacy, research, data and analytics, and business and operations are already or soon to be impacted. Within those functional areas, all types of stakeholders are engaging in AI strategy, including students, staff, faculty, and executive leaders.

With such far-reaching impacts, we also expect to see commensurate workforce changes. Indeed, more than half of respondents to our AI landscape survey said that they had personally been given AI-related responsibilities at work. Institutions are also beginning to formally restructure or redesign both leadership and non-leadership job roles to accommodate AI-related needs. Similarly, new positions are being created – not only in direct response to AI (e.g. chief AI officer, chatbot specialist) but also to support more general digital needs (e.g. chief technology officer, data scientist).

Taking action to create the future

It is vital that the higher education community has the information it needs to make data-informed decisions and plans for the future. Over the last year, we have published two AI-related action plans: on Generative AI and AI Policies and Guidelines. In these reports, we describe our experts’ vision of their preferred future of AI in higher education – a future in which AI outputs are representative and unbiased, AI supports access and accessibility, all stakeholders are able to think critically about AI tools and outputs, and AI is used to enhance human relationships rather than detract from them. We may never reach this ideal future, but aiming for it allows all of us to take intentional action, freeing us from a constant state of reaction. Finally, both action plans provide recommended actions for stakeholders at various levels. For example:

  • Individuals can experiment with and learn about AI technologies, create AI literacy resources, be good stewards of institutional data, and platform students’ voices and perspectives.
  • Departments or units can reimagine curriculum and assessment, invest in updating digital tools, foster collaboration, and reach across institutional silos.
  • Institutions can form AI-related committees and working groups, recruit AI experts, map AI policies and guidelines onto the institution’s mission and values, and include AI governance in a strong data governance strategy.
  • Multi-institution collaborations can establish cross-institutional AI research centres, share knowledge with the broader community, create a common understanding of laws and regulations (from local to international), and work with AI solution providers to meet the needs of higher education.

Most importantly, you can talk to colleagues and break down silos at your own institution and within your own professional networks. Start by asking: How is AI currently being used at our institution? How do we want AI to be used? What opportunities can we leverage to reach our preferred state of AI? What risks do we need to mitigate? You can also start by assessing your institution's generative AI readiness to facilitate these conversations. From there, you can create your own action plan to work toward the future of AI that you want to see and meet the unique needs of your own students, staff, and faculty.


Jenay Robert
Jenay Robert is a senior researcher at EDUCAUSE, a US-based non-profit association dedicated to advancing the strategic use of technology and data to further the promise of higher education. Her areas of interest include the future of education and work, equitable and inclusive education and work, social and cultural influences on teaching and learning, and ethical data practices.

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