Employers are not dropping resumes. They are adding ways to check what a candidate can actually do: work samples, skills tests, structured interview questions, and evidence drawn from past work. AI is entering this process mostly at the screening and matching stage, and sometimes inside online assessments. How far any of this has spread depends on the employer, the occupation, and the stage of hiring. Most of the hard figures below come from 2024 and 2025 surveys, so they describe that period rather than current hiring rates in late 2026.
What “demonstrated ability” means in hiring
“Demonstrated ability” is an umbrella phrase. It covers several different kinds of evidence, and AI scoring is only one possible way of gathering or reading that evidence. Employers that talk about skills-first or skills-based hiring usually mean some combination of the four methods below.
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Work samples
A work sample asks the candidate to produce something close to the actual job: a short analysis, a piece of code, a sales call outline, or a draft client memo. The value comes from the job-relevance of the task, not from its format. A sample is only useful if the employer defined what a good answer looks like before reviewing it.
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Experience has not disappeared as a signal. In the World Economic Forum’s 2025 survey of employers, the largest share expected to rely on work experience to assess skills during 2025–2030. What changes is how the experience is read: a candidate’s record of tasks, projects, and outcomes can count as evidence even when the job title does not match the posting.
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Skills tests
Skills tests may be timed, scenario-based, or delivered through an online platform. They can measure a narrow capability, such as spreadsheet modelling or typing accuracy, or a broader one, such as problem solving under a given set of constraints. Because they are often administered early, the test design matters as much as the score.
Evidence elicited in interviews
Structured interviews ask every candidate the same job-related questions and score answers against the same criteria. The evidence comes from the candidate’s account of specific past situations and what they did in them. This is the stage where the National Association of Colleges and Employers reports skills-based hiring is most common (see the table below).
How common the shift is
The figures below are not interchangeable. Each comes from a different survey, population, and year, and most measure what employers expect or report rather than what hiring managers did on a given day.
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| Measure | Figure | Source and date | What it covers |
|---|---|---|---|
| Expect to rely on work experience to assess skills | 81% | World Economic Forum, Future of Jobs Report 2025, expectations for 2025–2030 | Surveyed businesses’ expectations, not a count of observed decisions in every country or industry |
| Expect to use skills assessments | 48% | Same WEF report, 2025–2030 expectations | Same population; shares overlap because employers can use several methods |
| Do not assess prospective employees’ skills | 4% | Same WEF report, 2025–2030 expectations | Same population |
| Often or almost always use skills-first strategies | 34% | Society for Human Resource Management, 2025 | Organizations in SHRM’s survey |
| Interested in adopting skills-first strategies (among those that never or rarely use them) | 55% | Same SHRM survey, 2025 | Only the subgroup that does not currently use the approach |
| Use skills-based hiring at the interview stage | 90% | National Association of Colleges and Employers, Job Outlook 2025 (survey run August 5 to September 16, 2024; 237 respondents, including 162 NACE employer members) | Only employers that already use skills-based hiring |
| Use skills-based hiring in screening | About two-thirds | Same NACE survey, 2024 | Only employers that already use skills-based hiring |
The WEF and SHRM figures show a gap between intent and practice. Most employers in the WEF data expect to use some form of skills evidence, yet the SHRM survey finds only about a third regularly using a skills-first approach. The NACE figures are the most specific about where skills-based hiring happens, but they describe employers already committed to it, so they cannot be read as the share of all employers.
SHRM also reports that skills-first organizations were more likely to exceed financial objectives (35% versus 27%) and to report positive company culture (86% versus 78%). These are associations within the survey. They do not show that adopting the approach caused either result.
Where AI enters the process
AI is one tool inside the broader shift, and its role varies from employer to employer. Two broad patterns appear in the sources: AI helping to sort or match applications, and AI supporting online assessments. Neither means the employer has stopped reading resumes.
Screening and matching
Some employers use machine learning to match application data against job requirements, which can speed up the first pass through large applicant pools. Kara Yarnot, vice president of strategic consulting services at HireClix, told SHRM in a 2024 interview that “the technology is finally starting to catch up, and generative AI will unlock companies’ abilities for skills-based hiring, especially for early-in-career talent.” That is a vendor’s view of what the technology may enable, not an established finding about outcomes. SHRM’s 2024 talent acquisition trends coverage carries the quote.
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Online assessments can run before or alongside the interview. Whether the assessment is scored by AI, by a human reviewer, or by a fixed rule set is a question the candidate should ask, because the sources do not describe a single standard arrangement.
A company example: Amazon
Amazon has published a description of its own hiring process, including online assessments and machine-learning screening for some roles. This is one company describing its practice, not evidence of how most employers operate. Amazon’s account of its AI and ML hiring tools is the primary source for those details.
Do skills credentials change who gets an interview?
The Oxford Internet Institute’s Hire AI project surveyed 1,800 recruiters and HR professionals in the United States, the United Kingdom, and Germany, and studied how they responded to synthetic CVs. The project page reports that candidates with certified AI skills were significantly more likely to be invited to interview. The page does not give an effect size, so the finding shows direction only. It also concerns one credential type, one set of recruiter decisions, and three countries, and should not be generalized to all certifications or all jobs. The project page is the place to check the current description.
Transparency and perceived fit
A 2025 experiment in Information & Management by Chen, Han, Zhang, and Lu tested how people judged person–job fit under different levels of AI disclosure. It used a 2 × 3 design with 286 participants. The authors found that external and functional transparency about AI recruitment systems reduced differences in person–job-fit perceptions between AI and human evaluators. The study shows that disclosure can narrow a perception gap in that setting. It does not show that any particular system is fair, accurate, or unbiased. The article sets out the design and limits in full.
Five questions to ask about any hiring process
Because the methods differ, comparing them works best with a fixed set of questions. These five come from the dimensions that matter most for judging whether a process is measuring the right thing.
- What is measured? Credentials, past experience, a work sample, or a test. Each measures something different.
- Where does it happen? At application screening, at the interview, or in a later assessment.
- Is it job-relevant, and were the criteria defined in advance? A test with no stated standard is harder to defend than one tied to specific tasks.
- Does AI assist, rank, or decide? Assisting a reviewer is different from making the final call.
- Can a person review the outcome? Transparency about the process and a route to human review are the features the 2025 experiment examined.
Proving skills without the usual credentials
If you lack a degree, a recognized certificate, or a title that matches the posting, the strongest route is usually to produce evidence that a reviewer can check. The steps below work regardless of whether an AI system is involved.
- Map each requirement in the job posting to one specific piece of evidence. If a posting asks for data analysis, identify the dataset, tool, or report that shows it.
- Build one or two short work samples that resemble the job’s real tasks, and keep the inputs and your reasoning visible.
- Describe past work in terms of the task, the method, and the result, rather than only the job title.
- Prepare two or three specific stories from your experience that answer the structured questions a recruiter is likely to ask, and check each against the posting’s criteria.
- Before an online assessment, ask the employer what it measures, whether AI scores it, and how a candidate can request human review. If the employer does not answer, treat that as information about the process.
For a plain-language view of what AI tools can and cannot do in a job search, see the Associated Press’s tech tip on how AI can (and can’t) help you in your job hunt. For background on what skills-based hiring means, SHRM’s skills-first movement report explains the concept, and the OECD’s full report on promoting skills-first hiring and talent management covers the policy side.
The NACE data gives the most specific picture of practice: among employers that use skills-based hiring, the interview stage is where it is most common, with screening close behind. The WEF expectations suggest that work experience will remain a major input for many employers through 2030. Read together, the sources point to a broader set of signals rather than a wholesale replacement of the resume.
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