Educators say AI is becoming a vital life skill for university students

The quote lands like a dare in a group chat at 1 a.m. OpenAI’s Sam Altman says if he were graduating today he would feel like the luckiest kid in history. On TikTok, the clip gets stitched with side-eyed jokes from final year students who have two A level mocks next week and a part-time shift on Saturday. Luck is a nice word. Deadlines are real words.

Walk around any UK campus visit this term and you can feel the mismatch between how institutions announce AI and how teenagers already use it. A tour guide introduces an AI-enabled library search with the crisp rhythm of a product launch. Back in the cafeteria, two Year 13s compare the tone settings they used to rehearse interview answers, and laugh about how the robotic version of themselves sounded more confident than the actual one. No one asks whether AI is allowed in life. They ask where the line sits this week in coursework, exams, and personal statements.

Parents hover between optimism and audit mode. On WhatsApp groups, they trade screenshots of university policy pages like limited edition drops. One link promises equitable access to AI tools for all students. Another warns that detected AI writing in assessments could trigger an investigation. It is the same campus, two tabs. The thread ends with a screenshot of a job ad from a big employer that lists AI literacy as desirable. Nobody defines literacy. Everyone assumes the kids already have it.

Inside faculties, the tone is shifting from ban to blend. A computer science lecturer explains model biases like a weather forecast. A history professor says seminar prep can include a chatbot prompt if you also bring three primary sources that prove it wrong. In design studios, students are asked to start with AI sketches, then show what they chose to keep and why. Proof of judgment is the new proof of work.

Recruiters sound practical rather than prophetic. They rarely promise a map to the next decade. They talk about tasks, not jobs. What can be automated will be assisted first and automated later. What requires taste, negotiation, and consequence will stretch. The graduates who move fastest are not the ones who can make the most tools perform. They are the ones who can decide which tool belongs in which room.

All of this helps explain the quiet rebrand of certain degrees. Humanities courses are learning to sell what they always taught. Not Shakespeare as trivia, but close reading as calibration. Not philosophy as quotes, but argument as interface. If you believe AI will autocomplete more of our busywork, then the ability to name what matters is not an add-on. It is the operating system.

Mathematics retains its throne without needing to shout. The market has made it obvious. Data science and statistics sit in more prospectuses now, not only as majors but as minors or certificates that pair with everything from environmental policy to journalism. You can already see the brochures. Write better because you can model better. Model better because you wrote a tighter brief.

Meanwhile, student behavior has gone from novelty to norm. Revision notes are drafted in a chatbot, then annotated by hand in the margins like fossils from two eras. Practice interview panels happen in Discord where a friend plays hiring manager and a bot plays the curveball. The most coveted shared files in some school drives are not essays. They are prompt libraries with notes about what worked for OCR vs AQA vs the teacher who hates hedging.

Universities are responding at different speeds, which is why campus visits now double as policy tours. You can tell a lot from where AI shows up on the official pages. If it sits under plagiarism policies and nowhere else, students read that as a warning. If it appears in digital skills and careers, they read that as a promise. The most convincing signals are not slogans. They are course briefs that treat AI like lab equipment and assessment rubrics that reward human choices made in the presence of machines.

There is also the culture test. Does the campus punish experimentation in public or does it prefer everything to happen offstage, then arrive fully formed? Students can smell the difference in one afternoon. A university that hosts an open hack-day for AI in fieldwork is saying something about risk and play. A department that quietly pilots an AI co-pilot for feedback is saying something about capacity and care. Both are valid. Both tell applicants what it will feel like when work gets hard.

Employers are playing their own language games. Some job posts specify particular tools. Others avoid brand names and ask for evidence of workflow design. The subtext is simple. Show me that you can pick up whatever lands on your desk in 2027 and make it useful without breaking the rules or the team. Show me that you can spot the hallucination before it ships to a client. Show me that you can explain the choice you made to someone who did not sit in your seminar.

Parents ask if English literature or history still make sense in a world of auto-summaries and generated essays. The better question is whether a degree teaches the art of attention and the practice of editing. Can you notice when a neat answer hides a wrong assumption. Can you push back on a plausible sentence that contains a dangerous idea. The future will not lack for text. It will lack for judgment that scales without cruelty.

There is a softer layer to this too. Campus is where people learn how to be together under pressure. Group projects force a third path between lone genius and hive mind. AI can draft the agenda. It cannot make two strangers feel brave enough to argue in good faith at 10 p.m. in a seminar room that smells like leftover coffee. That social confidence is not a module. It is a memory bank you pull from later when a meeting goes sideways.

If you are choosing a degree now, the timeline is short and the noise is loud. The trick is to watch what institutions do, not only what they claim. Do first year modules include an explicit AI ramp so that students without laptops from Year 7 do not begin at a disadvantage. Do labs and studios show the provenance of training data so that ethics is not just a guest lecture in Week 9. Do careers teams partner with employers to run live projects where tool choice is part of the brief rather than a footnote.

On the student side, the vibe has settled into something like practical optimism. No one expects a syllabus to predict the job market in four years. They want a campus that teaches how to learn in public. They want permission to say I used a model for the first pass and then I rewrote it because it misunderstood the joke. They want tutors who mark the rewrite, not just the origin story.

There is pressure to pick once and for all, which the internet only makes louder. The reality is more fluid. Switching courses is not a failure. Adding a data methods module to a politics degree is not selling out. Taking a studio minor that forces you to show your work to real people before it is perfect is not a distraction. It is practice for a kind of working life where your first version will be produced in minutes and judged in seconds.

In that sense, choosing a degree in the age of AI is less about chasing a protected island of work and more about picking a place to build your habits of attention. It is about learning how to talk through a decision with people who disagree, while a tool whispers a shortcut in your ear. It is about becoming the person who can say that shortcut is wrong, and here is why, and here is a better one we can try.

The clip of Altman keeps circulating. Some students hear it as hype. Some as hope. Most treat it like weather. Useful to know, not a plan. They still have to hit submit on UCAS, still have to take the train to an open day, still have to decide whether the course feels like a room they want to be in when things get complicated. The luck, if it exists, is not in the toolset. It is in finding a place that lets you practice being the person who chooses well in public.

That is the part universities sometimes underplay. AI is the headline. Community is the infrastructure. The next four years will teach a cohort to make sense with each other while machines make suggestions. If the campus can hold that without panic, if it can invite teenagers into the messy craft of judgment, then the marketing line is true. Not because the tools are magic, but because the people using them might be.