Artificial Intelligence in human resources

Artificial Intelligence

Artificial Intelligence aids human resources in the screening, hiring, engaging, retention, developing, growing, and scheduling of employees (Miller, 2019). First, AI can be used to test the candidate before or after job application in an organization. Throughout the candidate screening stage, the primary role is to determine individual suitability and checking out data-driven measures of good fit through a strict screening. Candidates sourcing enables recruiters to find candidates who are highly qualified for the open position. Additionally, the attraction stage helps applicants apply for the job they are best at. The use of specialized chatbots is an example of AI candidate attraction process that is deployed to offer applicants the opportunity to ask questions. Natural Language Processing, NLP, is used to interpret and respond to questions asked by the candidates. The applicants can learn more about the company before they apply. Before applying for the job, most candidates do a lot of research about the company while considering the reputation of the brand, and most HR`S find candidate screening as a crucial stage in the AI. Candidate attraction enhances job matching as compared to old methods based on keyword searches. Thus, job seekers convert to job applicants (Miller, 2019).

Second, HRs’ consider using AI in the hiring process to ensure orderly and successful hiring (Miller, 2019). Hence, recruiters use AI in hiring to predict how long a job requisition will take to fill based on past data; therefore, they can rearrange as needed. For example, huge companies such as IBM developed IBM Watson Recruitment, IWR, a solution that uses AI to grasp information about the job market and ancient experiences of recruiting candidates (Miller, 2019).

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Thus, the IWR AI solution foresees the filling time and secludes the applicants that are most likely to succeed. Further, the IWR AI solution can also generate a predictive score based on biographical data, such as whether or not the applicant was a team leader in the resume. Thus, AI is crucial to recruiters hiring stage since it determines a match between the job requisition and the candidate’s resume (Miller, 2019). Also, AI in the hiring stage is essential as recruiters can make predication based on information gathered during an applicant’s job application stage. Since most recruiters are busy, AI assists recruiters to create time to focus on essential issues such as recruiting: nurturing, and building relationships with applicants (Miller, 2019).

engage stage AI

Third, for recruiters in the selection process, engage stage AI is crucial as it enhances motivation (Miller, 2019). In this case, AI is used by recruiters for two specific conditions; engagement analysis and talent alerts. First-line managers use AI talent reports as signs about their team members. Managers, with the help of AI talent notification, decide for the team members based on the vast information provided by the application of each team member and population of the workers in the company. For instance, depending on the needs of individual employees’ managers get promotion alerts that are customized. With specific skills and have been in the company for a long time (Miller, 2019). Moreover, AI engagement analysis is the technology that can inspect social media content within an organization. AI engagement analysis technology can analyze unstructured content from pulse surveys, yearly surveys, and social media chatter.

Equally, AI engagement analysis technology is used to discover instances of dissatisfaction among the employees through a unique sentiment analysis solution that analyzes manifold unstructured employee information. As such, the data is used to come up with a meaningful understanding of overall employee engagement, such as information sharing, training, and collaboration (Miller, 2019).

Nonetheless, the AI is required by recruiters for retention purposes during the selection process, which enables better compensation planning to be achieved by the organization (Eubanks, 2018). In essence, employee retention is dependent on factors such as the market rate for the staff’s skills, how in-demand the worker’s skills are, and if it is necessary to reward high performance in base pay or bonuses (Eubanks, 2018). Therefore, for recruiters to come up with ideal base pay decisions that match the employee’s experience, a broad comprehension of employee’s skills is needed. An example is the use of AI-powered decision and compensation support to avoid overweighing or underweighting essential data points (Eubanks, 2018). As such, the AI-powered decision and compensation support tool evaluates vast data points in making its references and understanding entirely external data from sources such as the Bureau of Labor Statistics (Eubanks, 2018). Hence, recruiters require the AI-based decision and compensation support tool as it makes sure that employees are not overpaid or underpaid: thus, minimizing bias. Also, the staff can classify their skills relative to the labor market as the AI-based compensation support establishes openness since the high and low range of bonuses for employees with their expertise is given (Eubanks, 2018).

AI is used by recruiters

Therefore, AI is used by recruiters during the selection exercise to guarantee development through personalized training (Eubanks, 2018). AI helps recruiters optimize learning at the level of the firm as well as speed up skill growth at the level of the employee. Recruiters apply AI tagging, where materials such as documents and images that are uploaded to learning management systems are fed with metadata through AI skills. Also, the AI technologies help the trainees to access the training content and utilize it frequently to achieve efficiency. For example, an AI-based learning ecosystem helps recruiters to understand what employers can do at their best, how they learn best, and what inspires them (Eubanks, 2018). Thus, recruiters are given a chance by the AI-based learning ecosystem to come up with internal applications that aid on-the-job education, allowing employees to acquire the need to learn. Additionally, recruiters utilize the AI-based learning as a leader in understanding and offering each employee’s recommended learning skills based on factors such as personality insights, preferences, job history, and career goals (Eubanks, 2018).

Summary of AI and its impact on recruiter’s selection process

Nevertheless, reviewers claim that AI chatbots are buying out human resources jobs (Eubanks, 2018). However, corporates that assimilate AI technology in the selection process supports that chatbots address fundamental questions, allowing HR professionals to focus on more complex HR issues (Eubanks, 2018).In fact, more jobs have been generated in the process of using chatbots that relate to designing and training of the bot (Eubanks, 2018). Hence, jobs are becoming more effective rather than fading: parts of the jobs that are disappearing are the regular tasks that can be automated. More importantly, HR’s situations that are upgrading, in essence, are impulsive, constructing, and analytical thinking. Primarily, AI technology talks about primary questions such as how the work to be done changes, and which area will change (Eubanks, 2018).

In response, critiques have debated that AI technology creates bias during the selection process (Eubanks, 2018). Nevertheless, AI technology has significant prospects to tackle bias if its developers are diligent on its design (Eubanks, 2018). Most companies adapting the AI systems for enrolment purposes and the organizations using the technology have a significant role to be aware of any bias. For example, candidate attraction and recruitment AI solutions develop a mindset switch in applicants about what is probable by validating jobs they did not know they were certified. As such, the AI systems specialize in skills in the endorsement and selection system. Thus, if a candidate has the skills required for a role, AI technology notifies the applicant about the task, irrespective of the applicant’s gender or ethnicity; hence, considering diversity (Eubanks, 2018).

Debunking the counter-arguments on AI and the selection process


Artificial Intelligence is essential in corporate organizations. The automation process helps in administrative and financial activities through the use of automated technologies and the execution of robotic operations. Besides, employees and customers are engaged as AI enhances cognitive engagement by natural language processing equipment (NLP). It is also essential as it uses cognitive insights that use an algorithm to signal vast volumes of data and interpret its meaning. Accordingly, Artificial Intelligence helps human resources in selection processes to attract, hire, engage, retain, develop, grow, and serve employees.

















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