How to Get Your First Job as a Graduate in the AI Era

Is AI really making it harder to get an entry-level job?

In some occupations, the evidence says yes, and it is worth reading that evidence carefully instead of trusting a headline. The most cited study is a working paper from the Stanford Digital Economy Lab by Erik Brynjolfsson, Bharat Chandar and Ruyu Chen, titled "Canaries in the Coal Mine?". Using payroll records from ADP covering millions of US workers, its first version in August 2025 reported that employment for 22 to 25 year olds in the occupations most exposed to generative AI had fallen by about 13% relative to less exposed groups. A revision dated August 2026 put that relative gap at 19%.

Three details matter. First, the authors say the change came mainly through reduced hiring of young workers, not through existing staff being removed. Second, they found no evidence of widespread, economy-wide job displacement. Third, in occupations where AI tends to help workers do the job, as opposed to doing it for them, employment was flat or rising. It is a working paper about the United States, and other forces such as interest rates were active in the same period.

Other sources point the same way on direction and are equally careful on scale. The International Labour Organization's 2025 exposure index estimates that one in four workers worldwide is in an occupation with some exposure to generative AI, and stresses that most jobs contain tasks that still need a person, so change is likelier than disappearance. The World Economic Forum's Future of Jobs Report 2025, a survey of over 1,000 large employers, projects 170 million jobs created and 92 million displaced by 2030. Those are employer expectations, not measurements.

What do employers want from graduates now?

The traditional entry-level deal was simple: a company hired beginners to do routine tasks, and the beginners learned the business while doing them. Drafting standard emails, cleaning data, writing basic code and answering common queries are exactly the tasks AI tools now handle passably. So employers are asking beginners to arrive ready for the next level: checking the tool's output, handling the unusual case, dealing with the customer.

The skills data backs this up. The World Economic Forum report ranks analytical thinking as the skill employers most often call essential, and says employers expect about 39% of workers' core skills to change by 2030. LinkedIn's Work Change Report estimates that by 2030 around 70% of the skills used in most jobs will have changed. PwC's 2026 AI Jobs Barometer reports that skills are changing more than twice as fast in the most AI-exposed jobs as in the least exposed.

Ask hiring managers what they look for in a beginner and three things come up repeatedly, and it helps to think of them as three corners of a triangle with proof of work in the middle.

How do I choose which jobs to apply for?

Applying to everything feels safe and works badly, because each role needs different evidence and different wording. Three target roles is a workable number: enough for options, few enough that you can build proof for each.

Start with patterns from your own life: which tasks made time disappear, what people ask you for help with, what you did that nobody required. Then build a long list of real job titles by looking at where graduates of your course went and by reading at least twenty live adverts. Score each role from 1 to 5 on interest, skills fit, number of openings, where it leads and how much the entry tasks rely on human judgement. Rank them and take the top three.

For each target, read ten adverts and note every skill that appears in four or more. Rate the level wanted against your level today. The biggest gaps on the most requested skills become your study list and the brief for your projects.

• Drop any title for which you cannot find ten live adverts within reach.
• Be cautious of lists of 'AI-proof jobs': they date quickly.
• Revisit your ratings after 30 days of real applications.

What portfolio projects should a fresh graduate build?

Three small ones, each with a different job to do. A good first-job project is real (real data, organisation or user), small (10 to 15 hours), matched to the role, has a result, and is written up so a busy stranger can follow it in three minutes.

Project one proves fundamentals: do the core task by hand. A business graduate might analyse twelve months of a local shop's sales in a spreadsheet. Project two is AI-assisted: use a tool to draft something, test it properly, and report what it got wrong. Project three involves a real person: present your findings to the shop owner and record what they decide to change. That third project is the one graduates most often skip and one interviewers like to ask about.

Write each up under four headings: Problem, Approach, Result, What I learned. Put a link on your CV and your LinkedIn profile. When an interviewer says "show me something you've made", you will have an answer.

Can I use AI tools in my job search without it backfiring?

Yes, if you stay in charge. A simple traffic-light rule helps. Green: use AI freely to explain concepts, quiz you, suggest ideas, check grammar and play the interviewer. Amber: when a tool drafts code, formulas or text that you keep, test it, understand every part and say so in one sentence in your write-up. Red: do not invent experience, do not let a tool answer a live test or interview for you, and do not paste private data into a public tool.

The disclosure sentence is worth more than it looks. "I used an AI assistant to draft the formulas, then checked 30 rows by hand and corrected two errors" turns a suspicion into evidence of judgement. Employers increasingly ask how you use these tools, and some add supervised rounds to check that the work is yours.

When you ask an assistant to improve your CV or interview answers, tell it to use only facts you supplied. Left alone, it may add achievements you do not have.

How do I get interviews when applications go unanswered?

Use more than one door and measure which works. Campus placements, company careers pages, job boards, internships, apprenticeships and direct approaches to small firms all produce hires. Record the source of every application, and after three weeks look at which source is producing replies.

Then spend at least a third of your time on people. A referred application arrives with borrowed trust. You do not need influential contacts. Alumni two to eight years ahead of you are usually willing to give fifteen minutes. Send a short message, under 80 words, that mentions your shared college, your target role and one project, and asks for advice instead of a job. After the call, thank them the same day and send a two-line update a fortnight later.

On the CV itself: one page, projects first, each bullet built as did what, with what, so what. Keep a master copy and tailor only the headline, the project order and a handful of keywords per application.

• Ten tailored applications a week usually beat seventy identical ones.
• Five new outreach messages a week is enough.
• Follow up once after seven days, then move on.

How should I prepare for aptitude tests, group discussions and interviews?

Screening tests reward timed practice more than talent. Find out the exact format, then do fifteen questions of one type a day on a timer, log your score, and write one line on every wrong answer: was it a concept, a careless slip or time? Twenty minutes a day for four weeks is about nine hours of focused practice.

Group discussions are not won by airtime. Assessors notice people who offer a structure, build on others, give an example, bring in a quiet member and summarise fairly. Practise with friends, record it and watch it back.

For interviews, collect eight stories from projects, studies, part-time or family work, community responsibilities and societies. Shape each as Situation, Task, Action, Result, and add what you learned. Say them aloud until they take about 90 seconds. A scored baseline can help here: AssessAll's Job Interview Readiness and Ready for Placement Week assessments show where you stand before you start.

How do I spot a fake job offer?

The US Federal Trade Commission's consumer advice puts the central rule plainly: honest employers will not ask you to pay to get a job. Registration fees, training fees, equipment deposits and "refundable" security payments are the commonest signs. Others include an offer with no real interview, pay far above the market for vague work, pressure to confirm within hours, free email addresses or lookalike domains, and requests to receive and forward money.

Verify through channels you find yourself. Go to the official website without clicking the link in the message, check that the email domain matches, look for the vacancy on the careers page or phone the main number, and show the offer to someone you trust. If you have paid or shared details, contact your bank immediately and report it to your national fraud reporting service. This is educational guidance, not legal advice; for bonds, deposits and contract clauses, check local law or a qualified adviser.

What does a realistic 60-day plan look like?

About ninety minutes a day, six days a week, in this order. The order matters more than the speed, and nothing in it guarantees an offer by day 60. What it does give you is evidence each week of what is working.

• Many applications and no replies: fix the CV or the targeting.
• Replies but failed tests: increase timed practice.
• Interviews but no offers: work on stories and fundamentals.