The best way to get hired for an AI job is applying directly to open postings that match your actual skills, because employer survey data shows the biggest barrier is a shortage of experienced, technically qualified candidates rather than a shortage of channels to apply through. Networking and referrals still help, but for a job that typically asks for a degree and specific tools, a well-targeted application into a live posting competes better than most job seekers assume.
Why do AI vacancies stay unfilled for so long?
AI vacancies stay unfilled mainly because employers cannot find candidates who match what the role asks for, not because postings go unseen. The UK’s Department for Science, Innovation and Technology commissioned a survey of AI employers in 2025, asking the ones with a hard-to-fill AI vacancy why it stayed open. A lack of suitable candidates topped the list, named by 39 of 64 respondents, ahead of competition from other employers, a lack of work experience, and a lack of specific technical skills.
That gap is closing. The same DSIT survey found the share of employers reporting a hard-to-fill AI vacancy fell from 69% in 2020 to 35% in 2025, and the share citing a lack of technical skills specifically dropped from 65% to 30% over the same period. Training and hiring have caught up with demand faster than most candidates assume. We analysed 678 live AI roles from companies hiring across Europe, and 37% ask for a senior, staff, principal or lead-level candidate, which lines up with the DSIT finding that experience, not applicant volume, is the constraint employers name most.
Which job search methods actually lead to an AI job?
Job postings and direct applications lead to more hires among people qualified for AI roles than personal networks do, which runs against the common advice that only networking works. Eurostat’s EU Labour Force Survey asks employees how they found their current job, broken down by education level, and the pattern flips as education rises.
| Highest education | Found job via job advertisement | Found job via personal contacts |
|---|---|---|
| Lower secondary or below | 14.5% | 42.8% |
| Upper or post-secondary | 25.5% | 31.7% |
| Tertiary (degree level) | 33.0% | 19.4% |
Source: Eurostat, EU Labour Force Survey, methods used by employees aged 25 to 74 to find their current job, EU aggregate.
Among people with a degree, the group AI roles are mostly drawn from, job advertisements outrank personal contacts as the route into a job. Word of mouth still matters. The same DSIT survey found it was the single most common recruitment method UK AI employers used to fill a role, named by 15% of respondents, ahead of social media at 13%. But it was one method among many rather than the dominant one, and a candidate skipping job postings on the assumption that only a personal contact gets them in is working from the wrong statistic for their education level.
Will AI screen your application before a human sees it?
AI increasingly screens your application before anyone reads it, so writing for a system as well as a person has become part of applying for an AI role, somewhat ironically. SHRM’s 2025 Talent Trends survey of 2,040 HR professionals found 51% of organisations now use AI to support recruiting, and among that group, screening resumes is the second most common use, after writing job descriptions, cited by 44%. SHRM’s survey fielded in February 2025 shows this has become mainstream practice rather than an edge case.
Inside the EU, that screening is now regulated. The EU AI Act classifies AI systems used to analyse and filter job applications or evaluate candidates as high-risk, with the main compliance deadline for these employment-related obligations landing on 2 August 2026. Employers deploying that kind of system have to meet accuracy and robustness requirements, including resilience against attempts to game the screening with keyword stuffing, so an application written in plain, specific language about what you actually did tends to survive both the algorithm and the recruiter reading the shortlist afterward.
Is an apprenticeship a realistic way into an AI role?
An apprenticeship is a realistic and fast-growing way into an AI role, though it still accounts for a small share of the people actually working in AI. The DSIT survey found the share of UK AI employers recruiting apprentices jumped from 3% in 2020 to 19% in 2025, the sharpest change of any entry route it measured. Graduate hiring grew too, from 42% to 60% of employers using that route, and remains the dominant path into a first AI role.
The apprenticeship route is newer than its adoption rate suggests. Employers who took on an apprentice in 2025 still report apprentices making up only 3% of their overall AI workforce, against 36% for graduates and 35% for professionals who moved into AI from an unrelated role. An apprenticeship is worth pursuing if it is on offer and a degree route is not realistic, but it is currently a smaller door than the growth in employer adoption implies, and a graduate route or a lateral move from an adjacent technical role still accounts for most people working in AI today.
Putting it together
Apply directly to postings that match the tools and experience you actually have, because the survey data above shows employers are limited by candidate fit more than by candidate volume, and a degree-level applicant reaches more roles through postings than through personal contacts. Write applications in plain language that a recruiter and a screening system can both parse, expect a senior-leaning market where experience is the scarcest input, and treat an apprenticeship or a lateral move from an adjacent role as a genuine option rather than a fallback.
Start with remote AI engineer jobs and remote machine learning jobs if you want to see what current postings actually ask for. Remote AI jobs across Europe and remote AI jobs in the UK cover the two country groupings the data above draws on most.