Plus, why the future of recruiting is equal parts human intuition and intelligent technology
In the quest to build high-performing teams, companies are always looking for an edge when it comes to hiring the best talent. Traditional interviews and resumes only reveal so much. But what if there was a more scientific, data-driven way to predict a candidate's likelihood of excelling in a role?
Enter psychometric assessments and AI-powered talent selection tools. These cutting-edge approaches aim to dig deeper into a candidate's strengths, weaknesses, personality traits, and potential—providing powerful insights to help employers make smarter hires. Here's a closer look at the fascinating science behind these game-changing hiring innovations.
Psychometric assessments have been used in corporate hiring for decades. But thanks to advances in behavioral science and technology, today's psychometric tools are more sophisticated and predictive than ever. Leading assessment providers harness huge datasets, machine learning algorithms, and rigorous validation to create tests that reliably forecast a candidate's:
Rather than relying solely on self-reported information from resumes and interviews, psychometric tests provide an objective window into the stable traits and competencies linked to high performance in a given role. Think of it like getting an "MRI" of a candidate to understand what really makes them tick.
For example, a sales position might benefit from a test that measures assertiveness, social confidence, goal orientation and resilience. Meanwhile, an engineering role may prioritize problem-solving, attention to detail and "stay with it" traits. By aligning the right assessments to key success factors in the job, employers gain a huge advantage in spotting candidates with the raw material to become top performers.
So just how effective are psychometric assessments at forecasting job performance? When developed using rigorous scientific standards, very effective.
In a landmark meta-analysis examining 85 years of research, psychologist Frank Schmidt and colleagues found that the best psychometric assessments can predict job performance with validity coefficients as high as .65. In other words, test scores accounted for a whopping 42% of the differences in performance between hires. That trounces the predictive power of resumes (.18), unstructured interviews (.38) and even years of job experience (.18).
"The value of psychometric testing is all about prediction. And the scientific evidence consistently shows well-constructed assessments are among the most accurate predictors of future job performance available. Nothing else comes close, frankly." —Dr. Charles Handler, Industrial-Organizational Psychologist and hiring expert
But psychometric tests aren't just about boosting the success rates of new hires. Used properly, assessments can also help to create a more fair, objective and unbiased hiring process. By focusing on job-relevant traits, skills and abilities—rather than pedigree—psychometrics help to level the playing field for candidates and minimize the impact of human bias.
Case in point: When psychometric pioneer SHL helped a major retailer re-vamp their hiring to be more inclusive and skills-focused, the percentage of minority hires jumped from 26% to 54% in customer service roles and from 32% to 57% in operations positions—with no adverse impact on job performance. Hires from non-traditional backgrounds ended up performing just as well or better.
If psychometric assessments provide an "MRI" of candidates, then AI-based talent intelligence platforms aim to be like an "fMRI on steroids." These high-tech tools leverage machine learning, predictive analytics, and huge datasets to uncover hidden insights and patterns that manual assessments might miss.
For example, leading AI platforms can:
The goal is to expand the lens on candidate potential—painting a richer, more holistic and bias-free picture than any single assessment or interview could provide.
"What AI enables is looking at people's capabilities and potential in much greater depth, at a far greater scale, and in a way that is much more fair and efficient than humans." —Ashutosh Garg, CEO of AI platform Eightfold
Some see AI tools as a threat to human judgment and discretion in hiring. But as The Economist notes, "AI will not replace recruiters. Instead, it will make them more productive and effective—and fairer." Indeed, studies find AI can significantly curb human biases in hiring, creating a more level playing field.
The results speak for themselves: When telecoms giant Vodaphone leveraged Eightfold's AI platform to help select software engineering candidates, the AI identified numerous "hidden gem" candidates—self-taught programmers from non-elite schools—who performed just as well as Stanford and MIT grads with flawless pedigrees. The shift to skills-based, bias-free AI selection helped Vodaphone double its hiring yield while cutting time to hire nearly in half.
As powerful as these predictive hiring tools are, experts caution they must be applied carefully and ethically. Psychometric tests and AI are not crystal balls. Nor should they be used as a magic bullet replacement for human judgment. Predictive scores must always be balanced with other key data points as part of a holistic hiring process.
And critically, employers must vigorously audit their assessments and algorithms for fairness and adverse impact. Amazon learned this lesson the hard way in 2018 when it had to scrap a recruiting AI that discriminated against female candidates. The system had been trained on historical hiring data in which men were overrepresented—causing it to systematically downgrade women's resumes.
But when developed and deployed responsibly, the combination of human expertise and intelligent assessment technology can be transformative—enabling employers to
