Articles 
Over the past years, the adoption of advanced artificial intelligence in recruitment has revolutionized the talent landscape. AI recruiting technology is now helping teams quickly find the most suitable candidates, eliminating the tedious manual review process and reducing potential human error or bias.
There’s no doubt that AI has the potential to transform how organizations manage talent. Compared to traditional recruiting processes, the advantages of a precise AI system are clear. Manually sifting through a vast pool of applicants can be overwhelming, especially for large corporations receiving hundreds or even thousands of applications for a single position. AI streamlines the hiring process and ensures hiring decisions are based on objective and accurate data.
Recent internal analysis of our resume parser by Avature’s Machine Learning team has shown impressive results in this sense: AI recommendations of candidates achieve an average accuracy of 80 percent. This means that out of the top ten candidates suggested by AI, eight are deemed relevant by human experts. Their analysis also revealed that its resume parser has achieved an average accuracy of 90 percent.
This efficiency in today’s competitive job market skyrockets productivity and allows recruiting teams to focus on strategic tasks, such as engaging with applicants and improving the hiring process.
Implementing AI-powered technologies saves time and enhances the quality of hires by promptly identifying the most qualified candidates. With features like intelligent job recommendations and skill-based matching that create a seamless and engaging experience, Avature’s AI tools offer a consumer-grade experience that improves user satisfaction for both candidates and TA and TM teams, increasing the likelihood of successful hiring and boosting employee retention.
Reducing Bias and Promoting Diversity with AI
As AI plays a more significant role in recruitment, concerns about bias in AI-led recruiting processes have emerged. Because AI systems learn from data, when used in recruiting these systems are trained on historical hiring information, resumes and job performance metrics. If the training data contains biases, such as a historical preference for specific demographics over others, the AI can perpetuate them.
Supporting bias-free hiring processes is a top priority for Avature, which is why our machine learning team has taken steps to reduce the potential for bias when analyzing large datasets to identify skills and aptitudes in candidates. This is done by excluding personal traits or historical human decisions from the input used to train it. Thus, by broadening the search spectrum, organizations are better equipped to find the talent they need while promoting diversity and inclusion within their teams, ultimately benefiting the entire organization.
Enhancing Candidate Matching and Decision-Making
Successful recruiting teams effectively match candidates with open opportunities, and AI can enhance this process in many ways. For instance, AI can rank candidates according to their fit with a position’s requirements, making it easier for recruiters to identify and evaluate the most relevant ones first.
Moreover, this technology enables recruiters to find similar candidates based on experience and skills, and provides historical information on similar positions to support more informed decisions. From the candidates’ perspective, AI can offer job recommendations and connect them with opportunities that match their profile, significantly enhancing the job search experience.
In this way, the Avature team constantly analyzes the impact of our tools and improves their accuracy to ensure that they remain on the cutting edge.
This article was originally published in Spanish by Equipos y Talento.
