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Generative AI in Higher Education: Academic and Student Perspectives
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15 June 2026
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Generative AI is rapidly reshaping higher education. In just a few years, AI tools have moved from novelty to everyday reality – influencing how students learn, how academics teach and conduct research, and how institutions think about assessment, skills and academic integrity. The pace of this change is extraordinary, and universities are now being challenged to respond in real time.
This moment presents both significant opportunity and profound responsibility. Higher education has always played a critical role in helping society navigate technological transformation. But unlike previous waves of innovation, Generative AI is evolving at a speed that leaves little room for passive observation or incremental adaptation. Institutions are being asked not only to understand the technology itself, but to make decisions about ethics, governance, pedagogy and workforce readiness while the landscape continues to shift beneath them.
The findings in this report show that adoption of Generative AI is already widespread among both students and academics. AI is embedded in universities across the world in their research, teaching preparation, assessment support and student study practices. At the same time, there is a clear and consistent message emerging from respondents around the world: universities must provide stronger ethical frameworks, clearer guidance and more practical support for responsible AI use.
Encouragingly, students and academics are broadly aligned on many of the sector’s priorities. Both groups recognise the importance of AI literacy, ethical capability and transparent governance. Students, in particular, are not calling for universities to resist AI, but to help them use it responsibly, professionally and effectively as part of their future careers and learning journeys.
The regional differences highlighted in this report are equally important. Perceptions of AI, levels of trust, and confidence in its role vary significantly across global regions, reinforcing the need for universities to balance shared principles with local context and institutional realities.
What is clear is that Generative AI is no longer a future consideration for higher education – it is already changing the sector. Universities that act early to establish ethical guardrails, rethink assessment, build institutional capability and embed AI literacy into teaching and learning will be better positioned to navigate this transition successfully.
At QS, we believe higher education has a critical role to play in shaping how AI is adopted responsibly and equitably around the world. Through initiatives such as the Responsible AI Consortium and the QS AI Capability Framework, we are committed to supporting institutions as they build the capability, governance and confidence needed to lead through this period of transformation.
Dr Maria Spies
Chief Innovation Officer
QS Quacquarelli Symonds
Read the report
Below, we've outlined the key findings and provided a sample of what to expect. Download the full report now for all the insights.
Key findings of the QS Generative AI in Higher Education report
- Generative AI is now mainstream in higher education. Two-thirds of academics (67%) and 62% of students use Generative AI at least weekly for teaching, research, study or administrative work.
- Familiarity with AI has increased sharply since 2023. Nearly half of academics (48%) and over half of students (53%) now describe themselves as extremely or very familiar with Generative AI, reflecting rapid adoption across the sector.
- Perceptions of AI are broadly positive. Most academics (74%) and students (68%) believe AI plays a somewhat or very positive role in society, with the strongest optimism reported in the Asia Pacific region.
- AI is increasingly embedded in teaching and research workflows. Academics are using Generative AI extensively for writing and editing support, lesson preparation, assessment design, feedback generation and literature summarisation.
- Students overwhelmingly want universities to integrate AI into learning. 94% of students say it is at least somewhat important for universities to incorporate Generative AI into the curriculum and learning experience.
- Assessment integrity is emerging as a major issue. Almost one-quarter of students (24%) report using AI to assist with essay writing, while 30% say universities should design assessments that are harder to complete using AI tools alone.
- Ethics, governance and data security are the sector’s top concerns. Academics identify ethical concerns, data security and the lack of institutional strategy and governance as the biggest barriers to effective AI implementation.
- Students and academics strongly align on institutional priorities. Both groups want universities to provide training on how to use AI tools professionally and ethically, alongside clearer guidance on acceptable and inappropriate use.
- Students are calling for responsible flexibility rather than restriction. While students support clearer policies and ethical guidance, many also want flexibility to use AI tools provided usage is transparent and appropriately disclosed.
- AI literacy is becoming a core graduate capability. Students increasingly expect universities to prepare them for an AI-enabled workforce through practical AI literacy education, ethical training and career-relevant applications of AI.
Academic familiarity and overall perception of Generative AI
Academics report a high level of familiarity with Generative AI. Nearly half (48%) describe themselves as either extremely or very familiar with the technology, while a further 44% say they are moderately familiar. This marks a significant increase from 2023, when only 30% of respondents reported being extremely or very familiar with Generative AI.
Sentiment among academics is also increasingly positive. Almost three-quarters (74%) say they view the role of AI in society as either somewhat or very positive, up from 68% in 2023. This shift suggests confidence is growing as AI tools become more widely understood and embedded in everyday practice – and as institutions begin establishing clearer policies, frameworks and guardrails around their use.
Regional differences in academics' perception of Generative AI
Regional differences are also emerging. Academics in the Asia Pacific region report higher levels of familiarity with Generative AI tools than their counterparts in Europe or North America, and are also the most likely to express positive views about AI’s role in society.
Student familiarity and perception of Generative AI in higher education
Students report even higher levels of familiarity with Generative AI than academics, underscoring how rapidly these tools have become embedded in student learning and everyday digital behaviour. More than half of students (53%) describe themselves as either extremely or very familiar with Generative AI - a notable increase from 40% in 2023. Familiarity and overall perception Students also continue to view AI positively overall. More than two thirds (68%) say they believe AI plays a somewhat or very positive role in society. While this sentiment has remained stable since 2023, maintaining this level of optimism amid the rapid evolution - and increasing scrutiny - of AI technologies suggests that students continue to see significant value and opportunity in these tools.
Conclusion
Across both surveys, a strong point of alignment emerges: Students and academics alike believe Generative AI should be integrated into higher education within clear ethical, institutional and pedagogical frameworks. While academics express concerns around ethics, governance, assessment integrity and data security, students are equally clear that they want transparent policies, practical guidance and education on responsible AI use rather than restrictive or punitive approaches.
The findings also demonstrate that Generative AI is no longer an emerging issue for higher education; it is already embedded in everyday academic and student practice. AI tools are now routinely used for research, teaching preparation, assessment support, study assistance and content creation. The challenge for institutions is therefore shifting from whether AI should be addressed to how universities can respond strategically, responsibly and at scale.
At the same time, the report highlights important regional differences in familiarity, trust and perceptions of AI’s role in society. As higher education becomes increasingly global and interconnected, institutions will need to avoid overly rigid or one-size-fits-all approaches. Instead, universities should establish shared ethical principles and governance frameworks that can flex across cultural, regulatory and institutional contexts.
A further theme running consistently throughout the findings is the growing importance of AI literacy as a core graduate capability. Students are not only using AI extensively today, but increasingly expect universities to help them develop the skills to use these tools critically, ethically and professionally in the workplace. This places AI capability alongside digital literacy, critical thinking and communication as an essential component of future-ready education.
Ultimately, the institutions best positioned for the future will be those that move beyond reactive policy responses and instead build coordinated, institution-wide approaches to responsible AI adoption. Universities that invest now in ethical frameworks, staff capability, authentic assessment design and practical student guidance will be better placed to protect academic integrity while unlocking the opportunities AI presents for teaching, learning and research.
Key actions
1. Establish clear institutional governance for AI
Universities should implement institution-wide frameworks for Generative AI that provide clear guidance on ethics, data security, acceptable use, transparency and attribution expectations. Governance approaches should balance consistency with sufficient flexibility for disciplinary and regional contexts.
2. Redesign assessment for an AI-enabled environment
Assessment strategies and academic integrity processes should evolve to reflect the realities of widespread AI use. This may include greater emphasis on authentic assessment, applied and in-class activities, oral defence, iterative project work, and clearer guidance on when and how AI support is permitted.
3. Embed AI literacy across the student experience
AI literacy should become a foundational graduate capability embedded throughout the curriculum. Universities should provide students with practical training on how to use AI critically, ethically and professionally, including understanding AI limitations, bias, verification and responsible decision-making.
4. Invest in staff capability and institutional readiness
Many academics identify skills, capability and resourcing gaps as barriers to effective AI adoption. Institutions should prioritise professional development, practical training and access to appropriate tools and support systems to help staff confidently integrate AI into teaching, research and administration.
5. Develop transparent and student-centred AI policies
Students are calling for clarity, consistency and transparency rather than blanket restrictions. Universities should co-design practical AI policies that encourage responsible use, support disclosure and transparency, and clearly communicate expectations to both students and staff.
6. Build adaptive strategies for a rapidly evolving landscape
The pace of AI development means institutional strategies cannot remain static. Universities should establish ongoing review mechanisms, sector partnerships and collaborative forums to continually evaluate emerging technologies, risks and opportunities as AI capabilities evolve.
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