Artificial Intelligence in Human Resources: A Case Study of Belong, Essays (university) of Artificial Intelligence

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AIAM Project Report

AI In hr hiring-Belong

Group 12

Anoop chaurasia- Ashvin Meena - 1711314 Jenish Kamdar - 1711022 Sachin Rajoria- 1711046

Introduction: “Land was the raw material of the agricultural age. Iron was the raw material of the industrial age. Data is the raw material of the information age.”- Alec Ross Artificial intelligence and machine learning innovations have been proven as a disruptive force in the field of industrial automation, medical science, aviation industry, marketing, gaming industry, education, telecom, and many more. Over the last decade, AI has crept into the realm of Human Resource (HR). Irrespective of its business vertical, having a right team in place is crucial for success for any firm. Therefore, it is essential to hire the best talent available to be ahead of the competition. Indian hiring industry, as per Executive Recruiters Association and Ernst & Young, worth Rs.35000 crores and growing at 21% 1 per year. The complexity of workforce challenges is also growing at the similar pace. Challenges faced by the human resource in an organization:

• Growing demand for novel skillset due to rapid digital transformation and business expansion across verticals and geographies which require a flexible recruitment process.
• Onboarding and adaptation to an unfamiliar environment by a fresh joiner are main areas of concern for HR. Because, if failed, all efforts in the selection, screening, and interviews processes get nullify.
• Fair and transparent performance evaluation of existing employees is an important function of HR since it is linked with the promotions and proper compensation. Along with technical and managerial knowledge, behavioral conduct is becoming a major factor in performance evaluation. Designing an evaluation matrix for behavior traits is a challenge for the HR team.
• (^) Elimination of biases in hiring, promotion. Language, religion, gender and appearance biases find their ways into giving selection and promotional preferences. In many cases, these biases are unconscious or unintentional in nature.
• Designing efficient knowledge and capacity building training modules for the employees is another challenging task for HR team because technologies in the market are changing with the lightning speed. It is imperative for employees to keep learning and gaining new skills.
• Hiring processes optimization which requires proper balance between time, cost and pool size of potential candidates. There is a trade-off between cost and talent selection process. Hiring is a most time and money consuming activity for any organization. It involves screening tons of resumes, interviews, onboarding formalities, skillset matching, suitable team and supervisor selection.
• (^) Identifying attrition patterns and using the insights to take corrective actions to increase the employee retention rate. Employee retention is as difficult a task as hiring talented employees for the HR team.

HR as a business vertical is going through a significant transformation in terms of its scopes and approaches. According to Deloitte’s report on India Human Capital Trends, around 53% 2 of firms are revising their HR policies to deploy digital tools, while around 22% of the surveyed firms are already leveraging artificial intelligence and data analytics to deliver HR solutions.

(^1) https://india.antalfranchising.com/the-recruitment-industry-in-india/ 2 https://www.vccircle.com/how-ai-and-machine-learning-will-impact-hr-practices/

Belong also helps in smart scheduling to identify the time slots to send the mails to the identified candidates so that there are greater chances of it being read. Emails in these time slots boosts response rates. Based on the responses, AI automatically buckets it into few categories. This helps the client in reaching out to the right candidates at right time. This saves a lot of time. Below is the picture showing how bucketing is done.

• Measure and optimize success: Artificial Intelligence is also being used for performance measures. Algorithms is trained to perform the appraisals without any bias and solely based on performance reviews. Being unbiased is the major challenge managers or supervisors face during performance evaluation. Also, AI is used to map the career paths of employees and put them on the track of career progression. Customized training and learning might be required for the employees which might not be possible for the supervisor to provide. With the help of AI, Belong now democratize individual specific initiative at appropriate timelines. Ai also analyses past performance and predict the future performances of individuals, teams or departments. HR directors can use this information to improve performance or boost morale.

framework followed by Belong:

After performing the necessary filtrations using AI technologies, the profile of the candidate

submitted by Belong to the client will look like this:

AI Technologies used by Belong:

• Machine learning : Consistently learning successes and failures — making data-driven predictions for selecting a right candidate.
• Big Data: Filters out relevant data from a vast pool for the desired qualifications of a candidate. Complicated data is made accessible and can be deciphered.
• Natural Language Processing : NLP can identify areas of development for each employee based on his/her appraisal results. Using this information HR can organize training or can provide better opportunities for development of the requisite skill sets.
• Behavioural pattern recognition: This gives the profiles of individuals’ behaviours. Helps in avoiding personal bias while selecting a candidate.
• Speech Recognition: This transforms & transcribes human speech into a language which is understood by the computer applications.
• Machine Learning Platforms: Provides algorithms, application program interface (API), training toolkits, and computing power for the design, training and deploying models into apps and other machines.
• Deep Learning Platforms : This special type of ML helps in pattern recognition and classifying applications which are supported by huge datasets. This consists of neural networks with many hidden layers.
• AI-optimized Hardware : AI-oriented computational jobs can be efficiently run by Graphics processing units (GPU) and specifically designed appliances.

recruitment team with solutions apart from the routine ones helping them to stay ahead of

competition.