What skills-based hiring data shows beyond the US and UK

You're in the room, defending a skills-based hiring push, when someone on the leadership team asks for the number. You reach for the usual one: a LinkedIn multiplier, or a headline stat from a US vendor report. It sounds authoritative, until someone asks what it actually measured. The honest answer is that WEF, LinkedIn's economic graph, eurostat and the BLS do not agree with each other.

Even the most basic figure, how many US job postings still ask for a degree, moves in opposite directions depending on which vendor counted it last. This piece lays out every sourced number behind the skills-based hiring story, region by region. That way, you can see where the evidence is solid. It also shows where it is one company's model dressed up as a fact.

TL;DR

• The one study that really measured hiring outcomes found dropping a degree rule moves real hiring by just 0.14 percentage points, roughly one extra hire in every 700.
• No country outside the US has a published rate of job postings dropping the degree rule; indeed, lightcast, cedefop and the OECD all study the topic without producing one.
• LinkedIn's widely quoted pool numbers, the bigger-pool figures for women, non-degree workers and AI roles, describe modeled pools of matching profiles, not people an employer really hired.
• Before you use any of these numbers inside your company, check whether it counts a job posting, a modeled pool, or a real hire. They are three different things, and public reporting treats them as one.

The US degree-requirement numbers contradict each other

Ask three vendors what share of US job postings still require a bachelor's degree. You get three different trend lines back. indeed's hiring lab reported the share falling to 17.8%, down from 20.4% five years earlier. A newer indeed update, covering data through november 2025, put the share back up to 19.3%, itself a rise from 16.6% two years before [1]. The publisher is the same. The methodology is the same. Yet the line moves in the opposite direction depending on which year you happen to read it in.

Every one of these numbers is an estimate pulled from free text, not a count anyone can audit. Deduplication makes them harder to compare still. lightcast strips up to 80% of the postings it collects within 60 days, then lets them expire. Indeed deduplicates for job-seeker experience, not for statistical accuracy [2]. Two vendors covering the same country in the same year are not necessarily counting the same thing. Treat every figure that follows, public or vendor-supplied, as provisional rather than exact.

No country outside the US has published degree-drop data

That clash is at least a debate between two numbers. Every place else, there is no debate, because there is no number at all. No source gathered for this report gives a share of job postings that dropped, or never had, a degree rule in canada, australia, ireland, any EU country, india, singapore, the gulf states, latin america, or africa. That is a gap in what has been made public, not in what the biggest vendors can measure.

Job-board vendors with global coverage haven't published the number

Indeed runs local job sites in dozens of countries. Yet its own degree-rule research has only ever covered the united states. Lightcast, a rival vendor, collects postings from more than 220,000 sources across 165 countries and already codes the schooling level needed on every posting it processes [2]. That means lightcast has the raw data sitting in its own database to publish a UK, german, or indian degree-rule rate tomorrow. Nobody has asked it to, and it has not done so on its own. Until one of these vendors runs the same study outside the US, "degree rules are falling" remains a claim about one country wearing a global headline.

LinkedIn's regional reports and the OECD add nothing on this specific question

LinkedIn's public hiring tracker, the one dataset that shows real hiring, not a modeled pool, covers only india, the UK, and the united states. Hiring happens everywhere else on LinkedIn's platform, but nobody is telling you what share of it involved a dropped degree rule.

The oecd's own 2025 synthesis on skills-first hiring reaches a blunt conclusion. The evidence across countries amounts to "little systematic evidence". It gives no figure for each country on degree removals, skills-based hires, or test use anywhere. Where the OECD does quote a number, it is borrowed from LinkedIn. That figure is given as an OECD-wide or global average, quietly blending US and UK numbers in with everyone else's. Read past the citation. The average turns out to rest on the same two countries every other figure in this report does.

Why skills-based hiring stalls in germany

Germany is the one place in this research where someone actually built a skills-based swap for the degree. Here the wall was not missing data. The wall was a workforce that would not accept the swap.

Germany tried to prove skills without paper, employers still wanted the paper

From 2019 to 2022, germany's public employment service ran MySkills, a computer skills test built for jobseekers who had no formal papers to show an employer. The idea was simple. People without a diploma would prove what they could really do, and that score would stand in for the paper. It did not quite work that way. Employers kept trusting a formal paper over a test result, even with the test result sitting right in front of them. The score became something caseworkers used in-house to decide who needed more training, not something that changed a hiring manager's mind. A tool built to replace the paper ended up serving the system that issues papers instead.

German law requires works-council sign-off on scoring candidates by skills, and no one tracks how often that slows things down

Even where a german employer wants to run a scored interview or a structured test, it may not be able to decide that on its own. The country's works constitution act requires the works council to sign off on standard hiring questionnaires, including structured interviews, before they go live. At companies with more than 500 workers, the council can also demand written proof of exactly which skills and papers the process is scoring for. That is a legally enforced brake on rolling out skills-based hiring in one of europe's largest job markets. No source tracks how many german employers have made works agreements covering skills tests. None tracks how much time that process often adds before a new hiring step can launch.

Bigger talent pools don't mean more hires

Move away from job postings and toward LinkedIn's own research. The numbers get bigger, and further from an actual hiring choice. LinkedIn's economic graph estimates that switching to a skills-first search expands the pool of matching people by nearly 10 times, on average, compared with searching by job title or direct work history [3]. That is a striking number. It describes a model run against LinkedIn's member database, not a company that really went out and hired ten times as many people.

The demographic breakdowns, non-degree, women, generation, AI roles, tell the same story: modelled pools, not hires

LinkedIn breaks that number down further. Workers without a bachelor's degree see their modeled pool grow 9% more than degree holders do under a skills-first search [3]. In fields where there are few women, the modeled pool of women grows by 24% [3]. Both are worked out the same way. You take a role, match people to it by skill instead of job title, and count how many more names show up.

LinkedIn also models a bigger AI talent pipeline under a skills-based approach. A separate LinkedIn study of who is really hired into the highest-paying AI roles found the opposite pattern. Those roles stay mostly filled by men who hold a degree. Put the two findings side by side. You get a clean picture of the gap this whole article is about. One number describes who could be found in theory. The other describes who a company still chooses to hire.

None of these figures has ever been linked to an actual hire

LinkedIn does track one outcome, its hiring rate metric, which confirms that a hire happened on the platform. It does not say whether that employer ran a skills test, used a structured interview, or hired someone without a degree. The pool numbers and the hiring rate are two datasets that have never been joined.

One study comes close. Peer-reviewed research tracked US LinkedIn profiles from 2015 to 2021. It found that workers who listed their skills had shorter gaps between jobs. That is a result. It describes a job seeker managing their own search, not an employer's hiring method, and it covers only the united states [3]. Nothing in the public LinkedIn data says who got screened out, interviewed, or hired because of a skill rather than a degree.

WEF future of jobs report 2025: 39% has no country data

LinkedIn measures the size of a candidate pool. The world economic forum's future of jobs report measures something else again. It tracks how fast the skills a job needs are changing underneath the person doing it. The 2025 edition projects that 39% of workers' core skills will change by 2030, down from 44% in the 2023 edition. Neither number comes with a regional breakdown. Neither one says anything about whether employers really test for skills when they hire.

Singapore is the one place with country-level confirmation

Singapore is the exception that proves how thin the rest of the data is. Research from the country's institute for adult learning found that every job in singapore saw its skill rules change between 2019 and 2024. Two separate government sources agree on that number, more backing than any other country in the WEF sample gets. Singapore's finding is specific. It simply cannot tell you what happened in germany, india, or anywhere else.

Everywhere else, the numbers are global averages from a sample too thin to trust by country

Every other figure in the WEF report traces back to one survey of just over 1,000 employers spread across 55 countries. Divide a thousand responses by 55 countries. Most countries are giving just a handful of employers each. That is nowhere near enough to support a number of their own. National bodies in australia and the european union repeat the wef's global figure in their own reports, but neither adds a local breakdown behind it. Treat every figure in this report except singapore's as a global average dressed up as a country's own headline, until the WEF publishes its data by country.

Dropping degree requirements rarely changes who gets hired

Every dataset so far has measured a job posting, a modeled pool, or a survey of intentions. Only one study asked the question that actually matters. When an employer removes a degree requirement, does the person they hire actually change? The answer is close to no. employers who dropped the requirement raised non-degree hiring by just 0.14 percentage points, roughly one extra hire in every 700 [4]. That single number settles a question the posting counts and pool multipliers elsewhere in this piece cannot answer on their own.

The best evidence we have, harvard and burning glass, found almost no effect

That finding comes from a joint study by harvard business school and the burning glass institute, built on more than 11,000 US job postings tracked from 2014 to 2023 [4]. Among the employers who genuinely removed a bachelor's degree requirement, non-degree hiring rose by 3.5 percentage points. The researchers then split employers into three groups based on what they actually did after announcing the change. Leaders made nearly all of the shift in hiring practice [4]. In-name-only firms announced the change publicly and then hired exactly as before. Backsliders saw a short-term bump. Then, within a couple of years, they hired fewer non-degree workers than before they had started. Only the leaders kept it up. Apple, walmart and general motors were the firms whose non-degree hiring kept climbing year over year, long after the announcement [4]. Study lead joseph fuller summed up what removing a degree requirement is worth on its own. In his words, it is "at best, the end of the beginning".

The other US numbers tell the same story, and nothing outside the US measures it at all

Payroll data backs this up from a different angle. ADP research, drawing on records for millions of US workers, found hiring for jobs that typically require a degree slowing sharply since mid-2022. Among US state governments that dropped their own degree requirements, bachelor's-required postings fell from 51.1% to 41.8% within a year. The researchers who tracked it work for the advocacy group pushing the reform. They say it is still too early to call the change lasting. No comparable check exists anywhere outside the united states. No one has matched a posting that dropped its degree requirement against who was actually hired for that role, in canada, the EU, APAC, latin america, or the middle east and africa [4]. Germany's MySkills program came closest. Even that tracked caseworkers' training referrals, not an employer's hiring decision. A job ad tells you what a company says it wants. Only a hiring record tells you what it actually did, and outside the US, almost nobody publishes that record.

Skills-hiring stats, with source, year and method

This table gathers the source numbers behind this piece, not the quick recaps and blog posts that copy them without the caveats. Public talk about skills-based hiring mixes four kinds of proof: job-ad counts, employer surveys, pool models, and worker mood surveys. Each answers a different question. None of them is a direct look at a hiring choice.

What the table shows, and where the sources actually agree and disagree

Line the sources up, and they agree on the trend: skills-based hiring is a bigger part of how firms talk about hiring than it used to be. They do not agree on how much it has changed who gets the job. Most of them were never built to answer that question at all. Read this table the way you'd read analysts' guesses before an earnings call: useful for the trend, not checked one by one, and worth far less as one headline number than as a pattern across all of them put together.

Cite this table, then build your own baseline

Cite this table on its own. Do not repeat a vendor's headline number. The source is Testlify, "what skills-based hiring data shows beyond the US and UK," 2026. It confirms what the public record actually supports. It also confirms how thin the evidence still is once you leave the US and UK. That gap, between what a job ad says and who actually gets hired, is the one our skills assessment platform is built to close. The platform turns a job description into a role-specific, proctored test in minutes, so your next hiring decision is measured, not modeled.

Pro tip: before you put any multiplier in a board deck, write down the one number you can defend without a footnote: how many people you hired last quarter, in the roles where you dropped the degree rule, who did not hold a degree. A pool size is a projection. A hire count is a fact, and it is the only figure in this piece that nobody can argue you out of.

Measure your own hiring, then compare

The gap this piece keeps returning to, between what a job ad asks for and who actually gets hired, is the gap a structured assessment closes. That is the thinking behind the Testlify Human+AI Evidence-Based Hiring Framework: score candidates on evidence you gathered yourself, then let a person make the final call. Testlify turns a job description into a role-specific, proctored test, so the shortlist is scored before the first call and the number you report comes from your own pipeline instead of somebody else's model. Book a demo and run it against one of your open roles.

Key takeaways

• The only study here that tracked real hires found that dropping a degree requirement moved actual hiring by 0.14 percentage points, roughly one extra hire in every 700. Treat that as your base rate: changing the job ad on its own does almost nothing, so budget for the screening change that has to follow it.
• No country outside the US publishes a rate for job postings dropping the degree rule. If a slide shows a European or Asian figure, it is almost certainly a global average painted onto one country, so ask which sample it came from before it reaches your board.
• Talent-pool multipliers such as 6.1x and 15.9x describe modelled pool sizes, not hires. They tell you how many more people could apply, never how many got the job, which makes them a sourcing input and a poor hiring-outcome target.
• Germany shows the limit of policy on its own. Employers kept asking for the paper credential even where skills were proven, and works-council sign-off on scoring candidates adds a step nobody measures, so plan a longer rollout in codetermined markets.
• The WEF 39% figure describes how much of workers' core skills are expected to change by 2030. It is not a degree-removal rate and not a hiring outcome, and quoting it as proof that skills-based hiring works is the most common error in this literature.
• Your own numbers beat every figure above. Track non-degree hires as a share of total hires in the roles where you dropped the requirement, measured against your own prior year, and you have the only evidence of progress that survives a hard question.

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