Designing the next decade of higher education
With changing skills demands, learner expectations and technological complexity, institutions must scale delivery while navigating ongoing disruption in higher education. A session, held in partnership with Instructure during the 2026 THE Europe Universities Summit, explored the critical priorities that could define institutions’ success in the digital era. The session outlined the risks of inaction and strategies for building a resilient, more connected and future-ready learning ecosystem.
Common challenges for universities include the demand for rapid transformation, rising learner expectations and the need to adopt complex technological ecosystems. “Higher education across Europe is entering a period of crucial change,” said Eumari Bonilla Cartier, regional director at Instructure. “Institutions are being asked to do more and scale very rapidly with small budgets,” Cartier said. They face increasing pressure to enhance teaching and learning using AI and accommodate different types of learners, Cartier said. “We often treat these as separate problems but in reality, they’re all interconnected.”
To navigate these shifts, institutions must address three core priorities: building a strong technology foundation and transparent technological foundations that support real-world learning; adopting purpose-built AI to move from fragmented experimentation to controlled, context-aware systems; and delivering flexible, modular and continuous education.
AI is no longer just a tool but part of the learning process, with 95 per cent of higher education students in the UK regularly using it in their learning journey, Cartier said. However, AI can cause users to develop a false sense of mastery by producing high-quality outputs without developing students’ knowledge. The focus must shift towards assessments that support learning integrity and long-term skill development.
While institutions grapple with evolving digital tools, learner expectations are being reshaped by consumer technology. Students expect flexible and personalised learning. “They want to learn anytime, anywhere and be supported by AI-driven tools,” Cartier said, adding that she often hears about “Frankenstein systems”, made up of multiple, disconnected platforms and solutions that fragment the user experience and are often difficult to manage.
Canvas, the learning management system (LMS) offered by Instructure, uses an AI model built to support education, mitigating the risks associated with mainstream AI models. “Institutions need visibility into how AI actually works, what data it uses and where it is applied,” said Cartier. “AI must be governed at the platform level instead of being adopted tool by tool.”
Instructure’s IgniteAI system is embedded within Canvas workflows and grounded in course context. It offers insights such as patterns in student engagement and suggests targeted interventions. Canvas is also available as an app for mobile access.
Systems must now also suit lifelong learning and microcredentials. “The labour market is changing so rapidly that it requires continued upskilling and reskilling,” Cartier said. Many LMS platforms cater to traditional full-time learners but future-ready systems need to accommodate this new landscape. This means facilitating short courses, stackable pathways and flexible access. Enrolment should be simple and match the speed and convenience of the consumer platforms learners use in their everyday lives. Strategy is no longer about predicting what the future could bring but about building an institution that is agile enough to adapt to the evolving needs of learners, Cartier concluded.
