AI for teachers: what it is actually good for

Almost everything written for teachers about AI is about students using it. Far less is about the teacher using it, which is where most of the immediate value sits and where the risks are much smaller.

The pattern that predicts whether a task will work: AI is good where you can judge the output instantly, and poor where you cannot. You know within seconds whether a comprehension question is well-formed. You cannot tell at a glance whether a historical date is right.

Where it genuinely saves time

Differentiating material you already have

Take a text or worksheet and ask for a version two reading levels down, or with the vocabulary glossed, or broken into smaller steps. This is the strongest use by a distance: the content is yours and already correct, the model is only reshaping it, and you can see immediately whether the reshaping worked.

Generating practice items

Twenty more questions in the style of the six you wrote. Quality is easy to check by reading them, and the failure mode is a dull question rather than a wrong one. Say the year group and the exact skill; vague requests produce generic filler.

First drafts of routine writing

Letters home, a description for a trip, the same information rewritten for a different audience. You will rewrite most of it, and starting from something is faster than starting from nothing.

Explaining a concept another way

When a student has not understood your explanation twice, a third framing helps and is genuinely hard to produce on demand. Ask for three analogies for the same idea and take the one that fits your class.

Feedback scaffolding

Not marking. Give it your rubric and a piece of work and ask what a student might be told about structure. Use it as a prompt for your own comments — you know the child, and it does not.

Where it wastes your time

• Facts you cannot verify at a glance. Dates, attributions, statistics, anything requiring a citation. Checking takes longer than looking it up yourself.
• Anything requiring knowledge of your specific class. It does not know which three students will find this hard or that last week's lesson went badly.
• Final grades. Beyond the reliability problem, a grade a teacher cannot explain is one they should not have given.
• Long documents where an error hides. A plausible schemes-of-work document with one wrong sequencing decision costs more to audit than to write.

The three-minute rule

If checking the output would take longer than doing the task yourself, do the task yourself. This resolves nearly every case.

Rewriting a worksheet for a lower reading level: checking takes a minute, doing it takes twenty. Worth it. Producing a timeline of a historical period: checking every date takes longer than writing the timeline from your own knowledge. Not worth it.

Prompting, briefly

Most disappointing output comes from a request that omits the context you were carrying in your head.

• Say the year group and the ability range. "Year 8, mixed, several working below" changes the output completely.
• Say what it is for. Starter, homework, assessment and revision want different things.
• Give it your example. One question you wrote is worth a paragraph of description.
• Ask for more than you need and select. Ten questions to choose four from beats asking for four.
• Push back rather than restarting. "Too wordy for this group, halve it" gets there faster than a new prompt.

On the honesty of it

Some teachers feel uneasy using a tool students are restricted from. That is worth taking seriously rather than dismissing.

The distinction that holds up: the student's task is usually to build a capability, so a tool that skips the effort defeats the point. The teacher's task is usually to produce material, and how it was produced matters less than whether it is right and suitable — which you are qualified to judge and the student is not.

That said, if a school expects students to disclose AI use, staff modelling the same disclosure is worth more than any assembly about honesty.