Candidate sourcing is the first and most critical aspect of the recruitment cycle. An organization may have dedicated recruiters to perform this activity. Few may also outsource it to agencies. However, the challenge in this process seems to be never-ending—mapping the skillsets required in JD to that of candidates from a list of hundreds, if not thousands. Be it recruitment portals or ATS; keywords are the most helpful tool to carry out candidate sourcing. In several scenarios, the 'gut-feel plays a more significant role than the experience and skills of the recruiter. To bring efficiency, several organizations have started leveraging the power of automation to screen the right candidate. In terms of technology, AI/ML-based tools are revolutionizing the entire recruitment value chain—especially the screening part that consumes the most effort.
Machine-driven CV screening
Resume screening to date has never been fast and accurate. Humans do make mistakes while screening apart from being unconsciously biased. Plus, it takes a massive effort to screen skillsets that 'really' match the job description. With an automated approach by next-gen platforms, resume screening has been incredibly fast, along with clinical level accuracy. AI-enabled ATS considers all aspects of a candidate's skillsets (recency, competency, industry, geography) before filtering out noise. The best part is that the machine only thinks objectively, taking out any account of biases or influences. As preliminary activities, a recruiter needs to set up rules in the ATS that are too customized for his requirement. AI/ML has garnered attention in candidate screening and the entire recruitment process, with remarkable outcomes.
Advantages of AI-driven profile screening
A modern-day recruitment process is powered by digital technologies to bring in higher efficiency and better outcomes. As more organizations embrace data-driven automation, resume screening will evolve into a commodity rather than a niche skill. Due to the higher demand for talent and diversified skillsets, AI-enabled recruitment platforms will gain popularity and adoption.
Time & Effort
Fulfilling an open position is an arduous task, further exacerbated due to a rising skills shortage. Firstly, there are thousands of suggested resumes with matching keywords, and only a diligent screening filters out unqualified of them—usually in a range of 75-85%. Screening such a vast list takes a lot of time and effort and is not the end of the tunnel. Only further down the process and with a high elimination rate during interviews, recruiters realize the pipeline needs even more filtered resumes to find the right candidate. Hence, the cycle continues. And, all these screening activities are only a part of recruiters' tasks apart from other day-to-day activities like scheduling, marketing job openings, or writing job descriptions. Adopting automated resume screening tools based on machine learning algorithms like iRekommend saves more than 60% on cost and reduces the possibility of bad hires. AI-enables platforms help source the best candidates from a pool of relevant skillsets and then screens the candidates using advanced analytics. Thus, it saves a lot of time for the recruiters to enhance their skills, participate in webinars and training, and improve the organization's standards.
Cultural Fitment
Just screening the candidates doesn't ensure that organization gets the right candidate fit for their culture. Many other aspects are critical to evaluation criteria and are only possible via data-based analytics driven by AI/ML technologies. Candidate engagements, interview results, and behavioral assessments all contribute to the holistic ranking of the candidates. An automated resume screening software performs such tasks with ease resulting in the hiring of the right talent.
Unconscious Bias
Selecting a candidate can sometimes be an emotionally biased decision rather than a logical process, hampering the recruiting process and the desired outcome. Biases can be in the form of gender, religion, community, location, or even education. On several occasions, the recruiter gets influenced by the candidates' subjective text on their resumes. Interestingly, these biases are not intentional, literally impossible to eliminate them. Machine scores big in this space. AI-driven resume screening is free from prejudices and acts only upon objective algorithms.
Diversity, Equity, and Inclusion
Organizations are increasingly looking for a diversified, equitable, and inclusive workforce. As a result, modern recruiting practices are embracing these strategies to deliver the right results for organizations. A machine-driven approach in the hiring process helps achieve these practices that might be too difficult for people-driven methods. It reduces the bias in the recruitment process and finds the right fit informed by data but driven by organizational priorities.
AI-enabled recruitment platforms facilitate the end-to-end hiring process right from talent sourcing to onboarding. Candidates become much more informed as the entire process is seamless, unbiased, fast, and transparent. With 360-degree feedback provisioning, it creates a positive brand image in candidates mind for the organization he is being hired. Most importantly, these platforms learn from previous interactions and better their suggestions for the next time. Be it a start-up or an enterprise; it is always best to automate the recruitment process—especially the resume screening activity.
At SimplyAI, we're building the future of recruitment powered by AI/ML to solve the most pressing recruitment problems of today's world.
We have accelerated talent acquisition while delivering as much as 25% cost savings to our clients against competing recruitment agencies.
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