Platforms, data, and artificial intelligence (AI) are impacting higher education systems and universities internationally. They raise challenges, including locking in institutions to corporate technologies, monetizing data, and interfering with academic governance. Future research is required to examine the concrete effects of platforms, data, and AI in context-specific settings, and to understand their underpinning political economy and future impact on international education and its constituents.

Platforms, data, and artificial intelligence (AI) are impacting higher education systems and universities internationally. They raise challenges, including locking in institutions to corporate technologies, monetizing data, and interfering with academic governance. This article examines some of these critical challenges.

Platformization

Higher education systems worldwide have developed digital ecosystems. These include digital infrastructure, which is often offered by Big Tech, such as Microsoft, Google, and Amazon Web Services, and organized via cloud services. University enterprise solutions, such as student systems, human resources, or customer management services, are provided by educational technology (EdTech) incumbents and are, in some places, being replaced with or moved onto cloud providers. A myriad of specific EdTech products and services are provided by digital platforms, such as virtual learning environments, digital libraries, and plagiarism-checking tools; they support teaching and learning, research, and institutional management. Many commentators call this profound transformation the “platformization” of universities.

Universities invest high amounts of labor and resources to make these digital infrastructures and platforms interoperable and to enable digital data flows within and beyond their institution. Ideas about the value of data motivate imaginaries of the digitally transformed university. The platformized university, it is argued, benefits from organizational efficiency, automating processes, personalizing learning, learning and business analytics, and scaling provision to larger audiences through digital formats like microcredentials, stackable degrees, boot camps, and the like.

Datafication

Such a digitally transformed platform university needs data. This includes merging administrative data, collected by universities from students, staff, and other organizations, and digital user data, collected by digital platforms as students and staff interact with various apps and software. Universities are building “data lakes” for data collection, aggregation, cleaning, processing, and the production of different data outputs that would support their aims. At the national level, many higher education authorities have created national or international higher education data systems to monitor higher education quality, support future skills management, and aid policy. At the higher education market level, EdTech companies aggregate student and staff data to innovate new products and services, or offer data insights and metrics, driven by their business models and data monetization strategies. Higher education is thus marked by datafication, a dynamic where activities, behaviors, and processes are turned into data to be analyzed and used.

There are increasingly new ways to define valuable data. Academic publishers have recently signed agreements with global AI companies to provide academic content to train large language models. The deals are worth millions to publishers, with AI companies gaining value from access to high-quality, standardized content to improve AI performance and offer new services. This poses significant downstream threats to academic research, teaching, and students’ learning, as automated “research” services are offered that can synthesize research literature, generate summaries, and even produce “original” academic articles or assignments. Both Big Tech and EdTech companies foresee AI becoming seamlessly integrated into all university activities.

Impacts

Platformization, datafication, and AI have profound effects on the higher education sector as a whole, all of its core practices, and its students and staff. This sectorial digital transformation is marked by shifts in the governance regime, as students and staff are required to accept terms of use issued by EdTech platforms, and universities sign long-term contracts with vendors, which are often hidden from stakeholders and the public and classed as commercially sensitive. These contractual lock-ins enable corporations to control data flows, set terms of use, and introduce new AI features, mostly without transparency and public scrutiny. Overall, this dynamic represents structural privatization of the sector, dominated by proprietary technology, and governed by contract and property law. While universities face legal, technological, and economic lock-in, individual staff and students face different kinds of challenges to their educational and social rights, with less room for collective action.

Future Research

Platforms, data, and AI in international education demand dedicated research to investigate their context-specific effects and the political economy that underpins them. Contextual studies should examine how platforms and AI are interweaving with existing educational practices in ways that reflect their political and economic contexts of application. For example, how is AI deployed in institutional settings marked by politically motivated attacks on academic freedom or diversity and inclusion policies? What kinds of big data are deployed to support institutional decision-making, particularly in contexts characterized by serious financial constraints and efficiency efforts?

Research on the political economy of big data and AI in international education should also seek to better understand the monetization of data through platforms, the extraction of value through infrastructure contracts, the political and economic drivers of AI, and the ways in which long-term subscription agreements act to “lock-in” institutions to contracts that serve private rather than public interests. At the individual level of students and academics, we should understand how they make sense of these new regimes of higher education governance via contracts and terms of use, as well as the effects on their agency and academic autonomy.

Janja Komljenovic is senior lecturer at the University of Edinburgh, United Kingdom. E-mail: [email protected].

Ben Williamson is senior lecturer at the University of Edinburgh, United Kingdom. E-mail: [email protected].