The rapid uptake of artificial intelligence in education has brought extraordinary possibilities for teaching, learning and institutional operations. Yet surrounded by enthusiasm for new platforms, pilots and digital tools, a crucial question remains easily overlooked: why is AI being adopted in the first place?

This conversation took place as part of Innovation Alley, where EduGrowth is delighted to bring education leaders into the EdTech conversation, creating a space for meaningful dialogue about the future of learning and innovation. The discussion featured Danny Liu, Professor of Educational Innovation at the University of Sydney, alongside two leaders at the forefront of educational transformation: Lee Barret, an educator and AI advocate within the Catholic Education Network across Australia, and Cherie Diaz, Executive Director Education Innovation at Western Sydney University.

Their conversation demonstrated that the future of AI in education is not, ultimately, a technological issue. It is a human question.

In many institutions, AI adoption begins with the tool rather than the purpose. However, teaching has always been an inherently relational, human-centred practice.

“Teachers want to improve student outcomes, yes but not at the expense of the relationships that underpin learning.” – Lee Barret

As Lee Barret highlighted, teachers want AI to strengthen pedagogy, not overshadow it. The aim is to support student outcomes while preserving the authenticity of classroom relationships. Effective AI use should reduce administrative pressures, expand creativity and provide time for deeper connection — not automate away the role of the teacher.

Cherie Diaz noted that in the university context, the rationale must also consider student readiness for the future workplace, appropriate use of data, and the efficiency of academic and research work. Although the operating environments differ, both perspectives affirm that AI is valuable only when it enhances human capabilities.

Although discussions about AI frequently involve teachers, researchers and technologists, important voices are still being overlooked.

In schools, parents and carers are often absent from the process. When invited into conversation, they express not only concern but genuine curiosity.

As Lee Barret observed:

“Parents don’t just want reassurance — they want to understand AI for themselves. They want to learn alongside their children.”

Meanwhile in universities, Cherie Diaz reminds us that leadership advocacy is needed. 

“Without executive alignment, pilots remain pilots. Leadership advocacy is essential to sustain momentum.”

Education transformation is therefore both a community and a leadership undertaking.

Every school and university has individuals who push forward new possibilities — sometimes well ahead of institutional readiness. These “earlier adopters” are invaluable, yet vulnerable.

Lee Barret mentioned:

“If we rely on individuals rather than systems, we risk burnout. Innovation must be supported, not left to survive on personality alone”

This requires redefining leadership roles. As Lee suggested:

“We talk about Assistant Principal for Teaching and Learning or Wellbeing — why not Assistant Principal for Curiosity?”

Innovation culture must be structural, not incidental.

Meaningful success in AI adoption is not measured in usage statistics alone. More significant indicators include:

• Reduced teacher workload
• Strengthened student agency and engagement
• Improved assessment alignment and learning design
• Scalability beyond early adopters
• Greater educational equity

Cherie summarised this clearly:

“Any initiative must begin with: What does success look like? And equally: What will we stop doing to make space for this?”

If nothing meaningfully changes, the technology has not driven transformation.

The discussion concluded with a shared vision. In ten years’ time, AI-enabled education should be:

• Personalised in a genuinely adaptive sense, not through fixed differentiation.
• Accessible, particularly for students with diverse learning needs.
• Human-centred, with teachers and students engaged in inquiry, creativity and exploration.

As Lee put it:

“The hope is that teachers and students are still doing brilliant, joyful things together and AI is simply present in the background.”

And perhaps most tellingly:

“Success is when we stop talking about AI altogether.”

In conclusion, artificial intelligence in education is not merely a technological initiative. It is a cultural, relational and ethical transformation. The question is not how quickly AI can be implemented, but how thoughtfully it can be aligned with the human purpose of education.

When the focus remains firmly on people, relationships and community, technology finds its rightful place, as a powerful support, not the centre of the learning experience.

Meaningful success in AI adoption is not measured in usage statistics alone. More significant indicators include:

• Reduced teacher workload
• Strengthened student agency and engagement
• Improved assessment alignment and learning design
• Scalability beyond early adopters
• Greater educational equity

Cherie summarised this clearly:

“Any initiative must begin with: What does success look like? And equally: What will we stop doing to make space for this?”

If nothing meaningfully changes, the technology has not driven transformation.