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Assessments through AI: Game-Changing Technology

Most of the HR recruiters agree; resumes don’t help judge the personality of a candidate in the true sense which is considered vital for his/her success in any organization. Based on just resumes, one might miss on several competent and well-adjusted candidates. In a survey by the prominent job search site CareerBuilder, it was found that a whopping 56% of recruiters have caught candidates lying in their resumes, mostly exaggerating their skills and abilities.

AI-based assessments have gradually made way into the recruitment process with the help of advanced candidate and employee psychometric assessments, from realistic chatbot-type conversations with candidates in situational judgment tests (SJT) to proven algorithm-based decisions made from looking at candidate responses against test questions. The use of AI in assessments is progressively supporting HR teams by being a valuable data-driven decision-making tool.

Pre-employment assessments powered by AI helps remove the guesswork from the hiring process. These tests, based on AI’s cognitive judgment, help assess if a candidate will be able to successfully perform the duties of the intended role. They also determine a candidate’s problem solving, quick thinking and data interpretation abilities. Leading employers like Starbucks and IBM are understanding the shortfalls of hiring talent via resumes alone and scrapping them to adopt a data-driven approach to talent acquisition.

A report by HR.com found that the areas of assessments where recruiters expect more involvement and results are - prioritizing applications and matching candidates to open positions. Automated assessments were also found to be the most important tool in talent acquisition in the same report.

The use of AI in assessment within organizations is not new. For years personality questionnaires have been scored and "interpreted" by expert-developed algorithms. The question now is how is AI improving the assessment process.

By analyzing large quantities of data through machine, the precision level of assessments is improving tremendously. Similarly, automated processes are making it faster and more efficient. Allowing AI to continuously learn by ‘observing’ the best practice of human raters offers the best and most legally-defensible approach for assessment by removing biases and also improving engagement through better candidate experiences.

  • Posted Date: 20-FEB-2020