Universities are investing in AI. But how do they compare globally?

Universities are investing heavily in digital technologies and AI, but many still struggle to integrate those tools effectively across teaching, research, and administration.

Ashley Mok
Vice President
Consultancy Services Times Higher Education

Huawei and Times Higher Education (THE) used the Asia Universities Summit at Hong Kong University of Science and Technology to highlight this challenge. Speaking at a joint Huawei-THE panel, Ashley Mok, Vice President for Consultancy Services at Times, summarized findings from THE’s Artificial Intelligence-Digital Maturity Index (AI-DMI), a survey-based framework developed in 2024 to help universities assess their progress toward becoming “future-ready” digital institutions.

The latest AI-DMI survey received responses from nearly 5,000 participants across 1,200 universities in 82 countries. Mok emphasized that the framework is intended not as a competitive ranking, but as a diagnostic tool to help institutions identify gaps in strategy, technology deployment, and organizational readiness. It evaluates universities across four dimensions: strategy, people, utilization, and technology; and it identifies four stages of digital maturity: incidental, intentional, integrated, and optimized.

Mok highlighted that many universities have clear digital transformation strategies, but effective use of technology often lags behind investment. In some advanced systems, including Singapore and Hong Kong, respondents reported high access to digital infrastructure but significantly lower levels of utilization, revealing a disconnect between the availability of technology and its effective use in teaching, research, and administration.

By contrast, some developing countries show the opposite pattern: limited resources but very high levels of utilization, suggesting that faculty and students are maximizing whatever digital tools they can access.

Mok said the white paper shows that many universities have built strong digital foundations with clearly defined transformation strategies but are struggling to make the next leap into AI-enabled education and research. While learning management systems and online platforms are now widespread, more advanced AI tools remain underused across functions.

Just 46% of respondents said they had access to personalized or adaptive AI learning platforms, and only 30% said they actively used such tools for teaching and learning.

The report also found that leadership commitment to AI is advancing faster than institutional processes. While nearly 70% of respondents said their universities encourage the use of AI and digital tools, many faculty and staff feel those skills are not yet reflected in hiring, promotion, or performance evaluation systems, highlighting a gap between the pace of AI adoption and the recognition of digital competencies.

The discussion also highlighted the broader strategic framework developed by THE in conjunction with Huawei: “Advancing Universities Towards an AI Future.” Introduced in an April 2026 white paper, the framework emphasizes aligning leadership, digital infrastructure, talent development, and ethical governance to support responsible AI adoption. It also outlines how universities can move from basic digital learning toward AI-enabled personalized learning models while expanding shared computing and research platforms to reduce gaps in AI capability.

The white paper can be accessed here: Advancing Universities Towards an AI Future

The Vice President of Huawei’s Education BU, Huang Chunxiao, said universities will play a defining role in shaping how AI develops and is used.

“Technology can give us power,” Huang said. “But only education can give that power meaning.”

Huang also stressed the importance of digital infrastructure, arguing that AI systems depend on stable, high-speed connectivity and shared computing resources. He cited Huawei collaborations with Beijing Institute of Technology and Shanghai Jiao Tong University as examples of how universities are integrating AI into teaching, research, and interdisciplinary training.