AI Literacy and University Readiness
Your Child Knows How to Use AI. But Do They Know How to Use It Well?
Ask a teenager whether they know how to use artificial intelligence and there is a good chance you will get a look that says:
Of course I do.
They may already use AI to explain difficult concepts, help with homework, generate ideas, summarise information, improve writing or answer questions faster than a search engine ever could.
To many parents, it can feel as though young people simply understand this technology instinctively.
After all, they grew up surrounded by technology.
But there is an important difference between knowing how to use AI and knowing how to use AI well.
And as AI becomes increasingly embedded in education, that difference may become an important part of being ready for university.
Knowing how to prompt AI is not the same as knowing how to learn with it
AI tools are remarkably easy to use.
You type a question.
You receive an answer.
Sometimes it is an extremely good answer.
That simplicity is part of what makes the technology so useful.
It is also part of what makes it complicated.
Because if a tool can explain the chapter, summarise the article, suggest the argument, improve the paragraph and provide the answer, a student has to make a conscious decision about how much of the learning process they are prepared to hand over.
That is a new skill.
Recent South African research into university students’ adoption of AI found generally positive attitudes towards the technology, but only moderate adoption overall. Importantly, AI adoption differed across faculties and levels of study, suggesting that there is no single, uniformly “AI-ready” university student.
In other words, being young and comfortable with technology does not automatically mean knowing how to use AI effectively in an academic environment.
The question is not simply: “Did you use AI?”
A more useful question might be:
“What did you use it for?”
Imagine two students preparing for the same test.
The first asks AI:
“Summarise this chapter for me.”
They read the summary and move on.
The second asks:
“Quiz me on this chapter one question at a time. Don’t give me the answer until I’ve tried.”
Same technology.
Very different learning.
One has asked AI to reduce the amount of work they need to do.
The other has used AI to make themselves do more of the thinking.
That distinction matters.
The OECD’s 2026 work on AI in education warns that students can sometimes produce better work with generative AI without achieving the same improvement in actual learning. If AI removes too much of the mental effort involved in understanding something, the finished task may look impressive while the student’s own knowledge remains much less developed.
Sometimes struggling with something is part of learning it.
That frustrating period when a concept does not quite make sense, when you have to reread something, wrestle with an argument or work through a problem is not necessarily wasted time.
It may be the part where the learning is actually happening.
AI can sound very sure of itself
There is another skill students increasingly need:
Knowing not to believe everything the machine tells them.
Generative AI can produce answers that are fluent, detailed and completely convincing.
It can also be wrong.
It can misinterpret a question.
It can oversimplify.
It can invent information.
It can produce references that do not exist.
It can confidently give you precisely the wrong answer.
That means the student’s job has changed.
Getting an answer is no longer enough.
They need to ask:
Where did this information come from?
Can I verify it?
Does it agree with credible sources?
Does this make sense based on what I already know?
Could there be another interpretation?
That is not just AI literacy.
That is academic judgement.
And academic judgement is something students need regardless of which technology they are using.
“But my child knows far more about AI than I do”
For many parents, this can be an uncomfortable part of the conversation.
Your child may genuinely know more about the technology than you do.
They may understand prompting, image generation, AI assistants and new tools you have never even heard of.
That does not mean you have nothing useful to contribute.
You do not need to know how every AI platform works to ask good questions.
You can ask:
“Do you understand the answer it gave you?”
“How do you know that information is correct?”
“Is your lecturer or teacher happy for you to use AI for this?”
“Did AI help you think, or did it do the thinking for you?”
“If you had to explain this without AI tomorrow, could you?”
That last question may be particularly useful.
Because the goal of education is not simply to produce an excellent assignment.
The goal is for the student to become more knowledgeable, capable and independent as a result of doing it.
Academic integrity has become more complicated
Once upon a time, the rules seemed relatively straightforward.
Do your own work.
Do not copy someone else’s.
Reference your sources.
AI has complicated that considerably.
Is it acceptable to ask AI to help brainstorm ideas?
What about improving grammar?
Creating an outline?
Summarising an article?
Rewriting a paragraph?
Generating the paragraph entirely?
Different universities, faculties, lecturers and even individual assignments may have different rules.
And those rules continue to evolve.
This means another important university skill is becoming increasingly relevant:
Do not assume. Ask.
Students need to understand the AI guidance that applies to their institution and their particular assessment.
If something is unclear, asking the lecturer is considerably safer than discovering afterwards that what felt like harmless assistance was regarded as inappropriate use.
Knowing how to use AI responsibly includes knowing when you are allowed to use it.
There are also things you should think twice about sharing
AI literacy is not only about assignments and academic honesty.
It is also about privacy.
Before uploading information into an AI system, students should develop the habit of asking:
“Should I be putting this here?”
Personal information.
Confidential research data.
Private correspondence.
Information relating to other people.
Unpublished work.
Sensitive institutional or workplace information.
The convenience of asking AI to analyse, rewrite or organise something can make it easy to forget that the information itself may need to be protected.
Again, the real skill is judgement.
So what does using AI well actually look like?
It might mean using AI to:
explain a difficult idea in a different way;
create practice questions;
test your understanding;
challenge an argument you are developing;
identify gaps in your reasoning;
suggest different ways of approaching a problem;
help structure a study plan;
brainstorm questions you should investigate further;
give feedback on clarity after you have written something yourself;
explore a subject before moving to credible academic sources.
And sometimes using AI well means not using it at all.
If the purpose of an exercise is to develop your own reasoning, writing, problem-solving or understanding, asking a machine to remove that effort may defeat the purpose of doing the exercise.
The question becomes less:
“Can AI do this for me?”
And more:
“Will using AI here help me become better at doing this myself?”
That is a much more powerful question.
AI is not going away
Students entering university now are likely to study, work and build careers in a world where AI is commonplace.
Pretending that the technology does not exist is unlikely to prepare them for that world.
Universities themselves are grappling with how generative AI should be integrated into learning, teaching and assessment. Internationally, organisations such as the OECD are increasingly treating AI literacy as a combination of knowledge, skills and attitudes, including the ability to critically evaluate AI outputs and use the technology
ethically and responsibly.
The opportunity, then, is not merely to teach students how to operate AI.
It is to help them develop the judgement to use it without surrendering the very abilities education is supposed to develop.
Critical thinking.
Curiosity.
Independent judgement.
Problem-solving.
Creativity.
The ability to recognise when something does not make sense.
The confidence to challenge an answer.
Those skills may become more valuable, not less, in an AI-rich world.
A thought for parents, students and schools
University readiness is changing.
It still means being academically prepared.
It still means learning to manage time, work independently, ask for help and navigate unfamiliar systems.
But increasingly, it may also mean understanding how to work alongside powerful technologies without becoming dependent on them.
For students, that means learning to use AI as a tool rather than allowing it to become a substitute for thinking.
For parents, it means recognising that you do not need to be the AI expert in the room to help your child develop good judgement around it.
And for schools and universities, it means that simply telling students to “use AI responsibly” may no longer be enough.
We may need to teach them what responsible use actually looks like.
At LSP, we believe preparation for higher education is about giving students a stronger frame of reference for the environment they are entering and the expectations they will encounter.
AI is rapidly becoming part of that environment.
The students who are best prepared for it may not be the ones who know the cleverest prompts.
They may simply be the ones who know when to use AI, when to question it, and when to close the screen and think for themselves.