By Matt Alder, host of the Recruiting Future podcast · Updated August 2026
Search for guidance on talent assessment and almost everything you’ll find is written by an assessment vendor ranking itself, or a review site monetising the comparison. This page draws instead on more than a decade of independent interviews with the TA leaders who buy and implement assessment technology, the scientists who build it, and the researchers who study whether it works. One finding keeps repeating across those conversations: structured, validated, explainable assessment beats resume screening and gut feel, but only when it’s built on a selection process you can explain.
AI has created a volume crisis at the top of the hiring funnel. Jobseekers’ use of AI means rapidly rising application numbers, and every applicant appears to have the perfect resume for the job. The resume was never a strong predictor anyway. Bas van de Haterd was arguing on the show for assessment at the front of the funnel as far back as 2018. He returned to the theme in 2019, pointing out that a resume has no predictive value whatsoever, and again in 2021. What AI has changed is the economics: when you can no longer skim-read your way to a shortlist, filtering on predictive data becomes the only workable response.
There’s a paradoxical upside here, and it’s the question I put to Tilburg University’s Djurre Holtrop in Ep 726: How AI Is Finally Killing The Resume: could AI be the solution to its own problem, democratising access to proven selection science and moving it to the top of the recruiting funnel? That’s where this is heading. Assessment is shifting from an optional mid-funnel step to the front door of hiring. The volume problem is reshaping the whole of talent acquisition, and I look at the bigger picture in the AI in Talent Acquisition guide.
Assessment is also the operational core of skills-based hiring. Many organisations have announced a shift from credentials to skills; far fewer have implemented it, and the honest ones will tell you why: assessing skills rigorously is the hard part (Ep 678: Assessing Durable Skills To Future Proof Hiring). You can’t be a skills-based organisation without getting assessment right.
Three changes stand out from my recent conversations.
AI interviewing has arrived, and trust is the battleground. Structured AI-led interviews can assess real skills at a scale humans can’t match, but candidates want to know when AI is evaluating them, how, and against what criteria. Transparency is becoming a selection criterion in its own right. I dug into this in Ep 807: Trust, Transparency And The AI Interview, and I make the wider case for honesty about AI in hiring in the AI in Talent Acquisition guide.
Candidates have AI too. Alan Bourne, an organisational psychologist who co-founded TalentQ and founded Sova, put it bluntly in Ep 705: Defending The Integrity Of Recruiting: candidates using AI are arguably winning the arms race against assessment. Anything text-based that a language model can read or hear can be scripted or answered in real time. That’s exactly what’s happening to interviews and hard-skill tests (Ep 591: Is AI Changing Jobseeker Behaviour?). The defensible ground is assessment that measures how people think and work rather than what they can look up: simulations, work samples and soft-skill measurement resist gaming in a way that knowledge tests no longer can.
Candidate experience now decides who you get to assess. Strong candidates abandon processes that feel like final exams. The research Charles Handler discussed in Ep 631: Science, AI & Assessment puts numbers on the intuition: engagement peaks at around 20 to 25 minutes, very short assessments read as less credible, and a candidate should never be left wondering why they’re being asked something. Done well, assessment becomes something candidates value rather than endure. Caitlin MacGregor described candidates thanking employers for the opportunity to be seen for what they could do rather than what they have done (Ep 701: Solving The Early Careers Crisis).
This is where independence matters, because the category’s marketing is loud and the claims are hard to check. The advice below is distilled from guests on both sides of the buying table:
The implementation stories on the show share the same shape as successful AI adoption more broadly: a specific problem, a defined process, humans kept deliberately in the loop. One of the strongest examples in the archive is Bell Canada’s work with HiringBranch on predictive hiring in high-volume roles, one of only two case studies I showcased in Ep 800: Will AI Break Recruiting?.
In Ep 722: Soft Skills, Hard Data, Veronique Lacasse and Stephane Rivard describe a process built the other way round from traditional recruiting. Candidates demonstrate the soft skills that drive performance up front, so by the time a recruiter speaks to them, the conversation starts from proven ability rather than resume claims. The process gets shorter too, which matters in a market where slow hiring loses candidates. Just as important is what happens after the hire. Recruiters see how the people they selected go on to perform, so every hiring decision gets checked against reality, and the whole system, human judgement included, gets more accurate over time. That feedback loop is the part most organisations never build. It’s what separates predictive hiring from screening convenience. Rivard’s earlier appearance, Ep 551: Interviewerless Interviewing, tells the origin story, including why candidates report feeling more confident showcasing their abilities in a well-designed scenario assessment than in a traditional interview.
One of the least discussed findings in the category comes from the Recruiting Excellence Foundation’s global benchmarking of TA maturity: across 21 components of the TA function, the two weakest worldwide are the job kickoff meeting and the hiring decision meeting, the moments where assessment evidence should be defined and then used. Most organisations’ assessment problem isn’t the test. It’s that they never agreed what they were assessing for at the start, and never structured how the evidence informs the final decision. Technology can’t fix either; process discipline can.
Assessment tools generate evidence; they don’t make hiring decisions. The judgement about what a role really requires, how to weigh conflicting signals, and whether a candidate will thrive in a specific team and culture remains stubbornly human, and per the benchmark above it is the least mature part of most TA functions. The organisations getting this right use assessment to make the human decision better informed, not to outsource it.
Watch three things. First, assessment moving earlier, to the very top of the funnel, as AI-generated application volume makes early filtering on predictive data unavoidable. Second, the convergence of assessment, interviewing and work samples into single, richer evaluations, including of human-AI collaboration skills. Third, a rising regulatory and reputational bar on transparency and explainability in AI-driven evaluation. The vendors that last will be the ones whose science survives scrutiny; for buyers, the advantage goes to those who could explain their selection criteria before they signed a contract.
Browse the Recruiting Technology archive, 333 episodes covering assessment and hiring technology, and the dedicated Assessment category.
Recruiting Future is an independent podcast for senior talent acquisition and HR professionals, hosted by Matt Alder since 2015. It publishes two episodes a week plus a monthly Round Up, and has published 882 episodes exploring AI, recruiting technology, recruitment marketing, employer branding, skills-based hiring, assessment and the future of work. Full details are on the about page.
Matt Alder is a talent acquisition futurist with over 25 years of experience across talent acquisition and talent strategy. He works with enterprise TA and HR leaders on AI readiness, has delivered keynotes in 18 countries, and is the co-author of Exceptional Talent and Digital Talent, both published by Kogan Page with Mervyn Dinnen.
Because this page discusses a vendor category, it is worth being clear about how the show operates. Recruiting Future is an independent production. It carries sponsorship from companies in the HR and talent technology market, at times including companies in the assessment space, and sponsorship is identified within every episode that carries it. Sponsors do not set the show’s agenda, its editorial positions, or its view of any product or category. Recruiting Future is not a review site and does not rank or recommend vendors, and nothing on this page is a product recommendation. Buyers should evaluate any vendor against the criteria above.
