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Skills assessments with AI - the complete guide to job simulations

Skills assessments with AI - the complete guide to job simulations

In this in-depth guide, we explore the revolutionary potential of AI-powered job simulations in the hiring process. According to an analysis by IBM Kenexa Talent Acquisition Benchmarking, companies using AI-powered job simulations saw a 67% decrease in the cost-per-hire.
Online job simulations are interactive tests that mimic real-world work situations, enabling employers to effectively assess candidates' skills. AI-powered job simulations have many benefits, including greater predictive validity, improved candidate experience, time and money savings, and less bias in the hiring process.
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The complete guide on assessments with AI includes:

  • Understaning job simulations
  • AI powered skills assessments
  • The benefits and challenges
  • How to implement it

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Artificial Intelligence (AI) integration in job simulations automates evaluation and scoring, resulting in reliable and impartial judgments. It promotes fair hiring procedures by reducing the possibility of bias and guarantees a realistic and job-related evaluation of candidates' talents. Organizations can now more effectively identify high-performing candidates and make data-driven recruiting decisions.
At sweeeft, 5+ years of R&D with active research and publications across CNRS, Liris, icar and LIG labs, make us the only solution to bringing AI machine learning to Human Resources. We assess candidates skills, personality, work style and more thanks to the analyses of 4 modalities: paraverbal (tone of voice), oral, written, non verbal (emotions). Each modality is linked to a skills library - this AI helps us run tests by combining all these factors together.
As technology continues to advance and the demand for skilled talent grows, job simulations with AI are likely to become even more prevalent in talent acquisition strategies. Organizations that embrace this innovative approach to skill assessment are better positioned to identify top-performing candidates, reduce hiring bias, and build high-performing teams. 
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