Hiremii is a platform that helps reduce the administrative burden of hiring by utilising Artificial Intelligence (AI) to simplify the recruitment process. It provides the user with an unbiased, accurate and efficient shortlisting service. There are some perceptions that introducing AI in the recruitment industry will take jobs away from current and future recruiters. However, studies emphasise that there will always be a need for the ‘human touch. Empathy and emotion are also required for cultural fit assessments, rapport building and negotiation (Ore & Sposato, 2020).
What is Artificial Intelligence (AI)?
Artificial intelligence are systems “that think like a human, act like a human, think rationally and act rationally” (Kambur & Akar, 2021). AI has the ability to solve hard problems rapidly with constant behaviours, detecting features in data that humans may not have the ability to conduct.
Benefits of AI in recruitment
Over the past couple of years, AI has been introduced in recruitment through filtering, pre-selection such as chatbots and the selection process. Research has shown that there are many benefits of recruiters using AI to assist them in their day-to-day activities, helping reduce repetitive tasks.
Using AI has been proved to help improve the candidate’s experience. Studies display that 49% of candidates mentioned that their chances of being hired improved. A result of this may be due to AI not having the ability to get to know a subject on a personal level. 56% of candidates felt that recruiters using AI removed biased actions (Anutej et al., 2022). Using AI also has the ability to speed up processes, this helps with the candidate’s experience as they do not wait long periods of time for the recruiter’s feedback. 80% of executives distinguished that the efficiency of recruiting improved. This could be a result of having more time to focus on the right candidates.
Reduction in recruitment costs
Research has emphasised that there is a 71% reduction in recruitment costs, helping improve productivity (Kambur & Akar, 2021).
Recruitment companies using AI can also help with employer branding. A recruiter has two main responsibilities, the first is finding the perfect candidate for their client. Their second is making sure the candidate is suited for the role. Using AI helps increase the chance of matching the perfect candidate for the role. This, therefore, helps reduce high turnover, improving the relationship with the clients. The communication between colleagues also improves when using AI, this can help increase motivation within recruitment organisations.
Improves the speed of recruitment
More than 60% of organisations that used AI mentioned that it increased speed. Further, studies have shown that recruitment companies that adopted AI saved 23 hours per hire. By recruiters not spending as much time on tedious tasks, it allows them to spend more time on building relationships, helping attract talent. Using AI can also help recruiters prioritise their time and resources on candidates who have potential. Further by using the AI, it helps improve both coordination and create strong connections between employees ‘dealing with distributed tasks” (Kambur & Akar, 2021). The below table further displays the improvements that AI has within the recruitment industry.
Overall, AI will help recruiters be more proactive in their roles throughout the hiring process. If you would like to research more about the topics discussed, the research papers can be seen below.
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Anutej, R. V. S., Padmaja, V., & Bhanumathi, P. (2022). Applicability of Human-Machine Interface and Artificial Intelligence in Recruitment: A Study. AIMS Journal of Management, 7(2), 242-265.
Kambur, E., & Akar, C. (2021). Human resource developments with a touch of artificial intelligence: a scale development study. International Journal of Manpower, 43, (1), 168-205. https://doi.org/10.1108/IJM-04-2021-0216
Ore, O., & Sposato, M. (2020). Opportunities and risks of artificial intelligence in recruitment and selection. International Journal of Organisational Analysis, 1934-8835. DOI 10.1108/IJOA-07-2020-2291