Keynote at Future Facing Learning and AI in Higher Education 2026

Apr 15, 2026

First slide from my keynote at Teesside University

On 15 April 2026 I gave the EdTech keynote at Future Facing Learning and AI in Higher Education 2026 at Teesside University in Middlesbrough. The talk asked a simple but increasingly urgent question: who will ultimately control the AI infrastructure that higher education is coming to depend on?

My session formed part of the conference programme on the opening day of the event, and focused on the fact that AI is no longer arriving in universities as a collection of isolated tools. It is becoming part of the background infrastructure that shapes teaching, assessment, student support, and institutional decision-making.

The live version of the keynote is available on AI in Higher Education.

Why this question matters

Universities are increasingly relying on AI capabilities delivered through platforms, cloud services, and software ecosystems owned by external organisations. That creates obvious opportunities, but it also creates dependencies.

In the keynote I argued that the sector needs to pay much closer attention to:

platform concentration and vendor lock-in
the mismatch between commercial incentives and educational values
data governance and institutional control
how models are evaluated before they become embedded in core academic processes
the need for collaboration across the sector rather than isolated procurement decisions

The central issue is not simply whether AI tools are useful. It is whether universities will act as passive customers inside systems designed elsewhere, or whether they will retain enough control to shape AI infrastructure around academic values, public purpose, and student interests.

Themes from the keynote

Some of the main themes I explored were:

AI is becoming infrastructure: the most significant changes are often the least visible, especially when AI becomes embedded in platforms institutions already depend on.
Dependency can accumulate quietly: each local decision about convenience, integration, or automation can deepen structural reliance on a small number of providers.
Governance matters as much as capability: procurement, evaluation, transparency, and accountability need to be treated as strategic questions rather than technical afterthoughts.
Higher education still has agency: universities can work together to develop stronger standards, better governance practices, and more public-interest approaches to AI adoption.

These concerns also connect closely with themes I write about on AI in Higher Education, particularly around vendor lock-in, misaligned incentives, and the role universities can play as a counterweight to extractive AI ecosystems.

Event details

Conference: Future Facing Learning and AI in Higher Education 2026
Date: 15 April 2026
Venue: Digital Life, Teesside University, Middlesbrough
Session: EdTech Keynote 1
Time: 1:30pm-2:15pm

You can view the official conference information on the conference homepage and in the programme page.

If you would like me to speak at your institution or event about AI in higher education, student voice, or the governance of AI-enabled teaching and assessment, you can get in touch by email.