Why international schools in Singapore & Hong Kong should teach AI in 2026

I have this conversation with heads of school more than any other, and it usually starts the same way.

"We know we need to do something about AI. We're just not sure what. Half our staff want to ban it, half want to embrace it, and nobody's quite sure what 'embrace it' even means in a classroom."

That's an honest place to start. So let me give you the honest version of the answer — the case for teaching AI in your school in 2026, what "good" actually looks like, and the worries that come up every single time.

The ban doesn't work — and it's the riskiest option

The instinct to ban is understandable. AI feels like a threat to academic integrity, and a blanket policy feels like control.

But here's what a ban actually does: it pushes AI use into the dark. Students don't stop using it. They use it at home, on their phones, on their own accounts, with no one teaching them when it's honest, when it's lazy, when the output is wrong, and when they're being quietly misled by a confident-sounding paragraph.

A ban doesn't remove AI from your students' lives. It just removes you from the room where they learn to use it.

That's the part I'd want every head of school to sit with. The students who most need an adult guiding their AI use are the ones a ban leaves most alone with it.

The future-skills case, stated plainly

I try to avoid the breathless "AI changes everything" talk — it's mostly hype, and you've heard enough of it. So let me make the narrow, defensible version of the argument.

The ability to direct an AI tool — to describe what you want, judge what comes back, spot when it's wrong, and refine until it's right — is becoming a baseline skill across most knowledge work. Not a specialist skill. A baseline one, the way using a search engine or a spreadsheet became baseline.

Your students will graduate into a world where this is assumed. The question for a school isn't whether they'll use AI. It's whether they'll arrive with judgement or without it.

And judgement is the word that matters. You don't get judgement from a policy document or a one-off assembly. You get it from doing — from making things with AI, getting it wrong, fixing it, and slowly developing taste for what good looks like.

What "good" actually looks like: build, don't lecture

Here's where most school AI efforts go sideways. They treat AI as a topic — a unit, a slide deck, a discussion about ethics and the future of work.

Those discussions have their place. But a slide deck about AI builds exactly as much real skill as a slide deck about swimming.

The version that works is build-based. Students make a real thing — and at Pathwise that thing is always a live, deployed web app with a URL they can send to their family. Not a worksheet. Not a poster. Something that works, on the internet, that they made.

When a twelve-year-old deploys their first working app and realises a grandparent overseas can open it on their phone right now, something shifts. The abstract becomes concrete. And concrete is where learning sticks.

If a programme can't point to a real artefact at the end of it, you're paying for theory. Theory about AI is an article. It isn't a programme.

The school offering, at a glance

When schools ask what working with us actually involves, this is the shape of it. We run on campus, across Singapore, Hong Kong, and the wider APAC region, and tailor the curriculum by age group.

The hackathon format is the one most schools start with, because it's the most visible — 200 to 500 students all building at once, every one of them shipping something by the end of the day.

The worries — answered straight

In my experience, heads of school and curriculum leads ask versions of the same three questions. Let me take them head-on.

"Is this just a fad we'll regret investing in?"

Fair. Schools have been sold "the future" before and ended up with a cupboard of interactive whiteboards nobody used.

The honest distinction is this: the tools change constantly — the specific app a student uses today may be replaced within a year. But the underlying skill — describing what you want, directing a tool to build it, judging the result — is stable. A good programme teaches that durable skill, not the tool of the month. So it doesn't go stale when the tools shift, because the tools shifting is exactly what we're teaching students to handle.

"Is it safe?"

The version that worries you — a student typing something inappropriate into an unsupervised chatbot — is a real risk of the unsupervised version. It's much smaller in a properly run classroom.

We use tools with content guardrails, our instructors monitor outputs through the session, and we're happy to walk your safeguarding lead through our safe-usage approach before anything starts. Many schools want that documented, and we provide it. The point I keep coming back to: the less safe path is the one where students use consumer AI alone at home with no adult teaching them how.

"Will it stop students learning to code?"

This is the one I hear from heads of computer science most, and I understand the fear. The honest answer is the opposite of what you'd expect.

Getting a student to a working app quickly is the single best thing for their appetite to learn fundamentals. Once they've shipped something real, they start asking "but how does this actually work?" — and that's the exact moment proper coding becomes worth teaching, because now they have a reason to care. Syntax-first, for most students, front-loads the boring part and loses them before the payoff. AI-first builds the motivation that makes the fundamentals land. It doesn't replace coding. It's the best on-ramp to it I've found.

How it fits what you already do

The schools that get the most from this don't treat AI as a new subject fighting for timetable space. They treat it as a tool students use to demonstrate learning they're already doing.

A sustainability-focused school themes the build day around "make an app that helps the planet." A school running a year-long inquiry maps the theme onto it. A STEAM-heavy school points students at "build a tool that solves a real problem you've noticed at school." The AI is the instrument; your curriculum is the music.

There's a future-readiness story in here too, and it's one you can tell parents and prospective families honestly. A school that teaches students to build with AI — rather than banning it or ignoring it — is visibly preparing them for the world they'll graduate into. That's a real differentiator at Open Day, and it's true, which is the only kind of claim worth making.

A note on cost

Schools ask about pricing early, and fairly. Programmes are scoped per school — a single year-group workshop and a whole-school multi-day residency are very different things — so the format and price are laid out in a written proposal after we talk, not pulled off a shelf.

If you want market context while you're scoping budget, our parent-facing price guides for Singapore and Hong Kong give a sense of what well-run, hands-on AI teaching costs to deliver. School programmes are priced differently, but the same principle holds: you're paying for real teaching, real tools, and a real shipped result — not a slide deck.

Where to start

The lowest-commitment way to find out if this fits your school is a discovery call. We'll ask about your priorities and your worries, you'll ask us anything you like, and we'll follow up with a written proposal a few days later. No pressure, and no slides on that call.

Or browse the full menu of school programmes — whole-school hackathons, weekly afterschool, holiday camps, and teacher PD — to see what shape might fit your campus. If you're weighing this for the adult or corporate side of your community too, /companies covers that.

You don't have to have AI figured out before you start. None of us did. You just have to decide your students are better off learning it with you in the room than without you.

— Mr. Brown