Don’t just use GenAI; struggle with it!

Dr Guy Bate

GenAI is unsettling the routines of education. It is not just changing what students produce, but also how learning unfolds and how teachers define their roles. As generative tools spread, the risk is that we use them primarily to speed up existing practices rather than rethink them.

This short piece considers the three practices that I recently introduced in a provocation essay for AI & Society — reflection, struggle, and wayfinding (Bate 2025) — to stimulate ideation among educators and edtech developers seeking to engage more deliberately with GenAI.

Reflect: AI can reveal what is already embedded in how we teach

Ask a model to write an essay or plan a lesson, and it often produces something plausible but uninspired. This isn’t a flaw in the technology. Rather, it reflects what it has learned from us. The outputs are shaped by dominant patterns in educational content: what we assign, how we assess, and what we reward.

For educators, this is not just a prompt to evaluate GenAI, but to re-examine our own practices. If GenAI generates responses that meet our criteria but feel empty, perhaps the criteria themselves need questioning. Are we privileging standardisation over creativity? Clarity over complexity? Output over process?

For developers, similar reflection applies. What pedagogical assumptions are embedded in the tool’s design? Are you encoding norms that reward predictability and compliance, or enabling educators to surface and interrogate those norms? Tools that merely replicate what already exists risk reinforcing blind spots unless they also support deeper insight.

Struggle: The friction is the learning

One of GenAI’s most generative effects is the discomfort it causes. When an output feels off, it creates an opening. Why does this version not work? What would make it better?

For teachers, this discomfort can sharpen their own and students’ critical skills. Comparing human and GenAI-generated responses helps clarify expectations, surface tacit knowledge, and deepen engagement. Educators can model how to evaluate nuance and voice, not just correctness.

For developers, designing for this friction means resisting the urge to over-polish. Instead, build tools that support revision, disagreement, and dialogue. The goal is not seamless answers, but more thoughtful thinking.

Wayfind: Use GenAI to explore, not just execute

Too often, GenAI is treated as a shortcut to a finished product. But its greater value lies in exploration. It can help test alternative framings, shift perspectives, and simulate different worldviews.

For educators, this opens new possibilities. Ask the GenAI to present a case study from a different cultural lens, or to challenge a student’s assumptions. The point is not to settle the question, but to open it up.

For developers, this means designing tools that invite branching, not closure. Exploration and ambiguity are not problems to fix, but conditions to support.

Where next?

As I have said before, the future of GenAI in education will not (and should not) be decided by technology alone. It depends on how we choose to engage with it: will we replicate what we already know, or reimagine what it could become? How can we design GenAI-enhanced learning that challenges outdated norms and opens space for more human, more creative, and more meaningful forms of education?

Let’s not just adopt GenAI. Let’s struggle forward with it.

Reference

Bate, G. W. (2025). The struggle is the lesson! Being an educator in the age of AI. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02347-1

Bio:

Guy is Thematic Lead for Artificial Intelligence, Director of the Master of Business Development (MBusDev) programme, and Professional Teaching Fellow in Strategy and Innovation at the University of Auckland Business School. With two decades of international industry experience in health technology, biotechnology and pharmaceuticals, Guy has held leadership roles in strategy, business transformation, and new product development.

A passionate advocate for the transformative power of AI in teaching and learning, Guy is a frequent speaker and workshop facilitator for both academic and practitioner audiences. He focuses on using AI to enhance student engagement, facilitate personalised learning, and foster self-directed development.

Guy holds PhD degrees in both Management and Biomedicine and is a Fellow of the Royal Society of Biology in the UK (FRSB), a Fellow of the Higher Education Academy (FHEA), a Certified Management & Business Educator (CMBE), and a Member of the Institute of Directors in New Zealand (MInstD). He chairs the AI in Education Technology Stewardship Group for EdTechNZ, and also serves on the Committee for ASCILITE’s Business Education Special Interest Group and on the Advisory board for Grow Tourism, an NZ-based digital learning provider.