New UNESCO IESALC study reveals widespread AI adoption in higher education across Latin America and the Caribbean, while governance lags behind

Artificial intelligence is rapidly transforming how higher education institutions teach, learn, conduct research, and operate. Yet while AI adoption is becoming increasingly widespread, governance frameworks and institutional strategies are struggling to keep pace.

These are among the key findings of AI Implementation in Higher Education in Latin America and the Caribbean, a new report launched by the UNESCO International Institute for Higher Education in Latin America and the Caribbean (UNESCO IESALC), with the support of the United Nations University Institute for the Advanced Study of Sustainability (UNU-IAS), during Digital Learning Week 2026 at UNESCO Headquarters in Paris.

The study draws on data from 200 higher education institutions across 19 countries in Latin America and the Caribbean, offering a unique evidence base on how AI is being integrated into teaching and learning, research, administration, community engagement, and institutional governance.

AI adoption is already widespread across the region, with 87% of institutions using AI in at least one area of their activities. AI is most commonly used in teaching and learning, with 74% of institutions reporting its use, often through general-purpose tools such as ChatGPT, Copilot, and Gemini. AI is also playing an increasingly important role in research, with 57% of institutions reporting its use to support data analysis and enhance research quality.

Despite this rapid uptake, the document highlights a significant governance gap. Only 26% of institutions have a formal AI strategy in place, and even fewer have established clear policies, governance structures, and monitoring and evaluation frameworks. In many cases, AI adoption is being driven by faculty members, researchers, and students rather than by institutional policies or strategic guidance. Moreover, while staff training on AI is common across the board, training for students is lags behind with 1 in ever 2 students reporting confusion about appropriate AI use.

The study also identifies disparities across the higher education sector. Private institutions tend to lead on all dimensions, particularly strategic planning, staff training, and governance, while public institutions often face greater resource and capacity constraints. These differences raise important questions about equity and access, both within higher education and across society more broadly.

Institutional leaders surveyed for the report identified staff training and AI advocates within their institutions as the most important drivers of adoption. At the same time, insufficient funding, limited expertise, uneven training opportunities, and concerns regarding data privacy, bias, and academic integrity were cited as major challenges.