Scaling What Matters: Using AI to Personalise Teacher Development

Sponsored content by IRIS Connect.

Everyone agrees that teacher development matters. So why is it still so hard to do well, at scale?

Schools invest time, money, and energy into professional development, yet many leaders quietly admit the same frustration. The learning is uneven. The impact is hard to sustain. And the teachers who would benefit most often have the least time to engage.

The problem is not commitment. The problem lies in how professional development is designed.

The uncomfortable truth about professional development

Effective professional learning is personal. But most systems are not built that way.

Teaching is complex, situational, and deeply human. What works in one classroom can fail completely in another. When professional development becomes overly standardised, it may be easier to deliver, but it loses relevance. Teachers are asked to adopt techniques without the space to interpret, adapt, and reflect.

That is where the tension sits. Personalisation leads to impact, but personalisation is difficult to scale. Or at least, that has been the assumption until recently.

Why scale has been the enemy of quality

To reach more people, systems often simplify. Frameworks become checklists. Reflection becomes compliance. Coaching becomes episodic rather than sustained. The intention is good, but the result is familiar: activity without depth.

Meanwhile, the most powerful driver of improvement often receives the least sustained attention. Supporting teachers to get slightly better each year does not just create short term gains. It compounds. Over time, it shapes professional culture and classroom practice in ways no single initiative can.

The question is no longer whether this matters. The real question is how to make it possible.

Where AI changes the conversation

AI is often framed as a shortcut. That framing misses the point.

Its real potential lies in reducing friction, not replacing thinking. Used well, AI can help teachers and leaders make sense of practice, highlight patterns worth exploring, and focus attention where it is most needed. It can support reflection and dialogue without prescribing answers.

This matters because reflection is rarely resisted. Sustaining it within limited time and capacity is the real challenge.

When technology removes the barriers that make reflection difficult to sustain, personalised professional learning becomes more achievable, even across large teams or trusts.

Personalisation without losing coherence

The concern is understandable. If development becomes more personalised, how do you maintain shared language, alignment, and direction?

The answer lies in structure that guides without constraining. When professional learning is grounded in clear development pathways and shared frameworks, AI can support individual growth while keeping everyone moving in the same direction. Coherence comes from clarity of purpose, not uniform delivery.

Making what matters easier to do

The aim is not to increase the volume of professional development. The aim is to improve its quality and make it sustainable.

This is where platforms like IRIS Connect focus their effort. By combining video, structured reflection, collaborative learning, and AI driven insight, schools can support meaningful development without adding workload. The technology does not lead the learning. It enables it.

When AI is used to amplify professional judgement rather than replace it, scale no longer has to come at the expense of quality. And teacher development stops being something schools aspire to do well, and starts becoming something they can sustain.