ISSN: 2641-3086
Trends in Computer Science and Information Technology
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Talent Recruiting Innovations and High Start-Ups

Sehar Shahzad Farooq1*, Irfan Mehmood2 and Soon Ki Jung1

1School of Computer Science and Engineering, Kyungpook National University, Daegu, Korea
2Lecturer Applied Artificial Intelligence, Faculty of Engineering & Informatics, University of Bradford, United Kingdom
*Corresponding author: Sehar Shahzad Farooq, School of Computer Science and Engineering, Kyungpook National University, Daegu, Korea, E-mail:
Received: 22 September, 2020 | Accepted: 05 October, 2020 | Published: 06 October, 2020

Cite this as

Farooq SS, Mehmood I, Jung SK (2020) Talent Recruiting Innovations and High Start-Ups. Trends Comput Sci Inf Technol 5(1): 065-066. DOI: 10.17352/tcsit.000025

The talent management market is increasing rapidly, and the software and platform part of the market consists of recruitment tools, job interviewing tools, social media advertising, assessments, and Artificial Intelligence (AI) based systems [1]. The growth in talent recruiting is driven by the recent innovations in AI such as deep learning and convolutional neural networks [2]. Current, AI-based solutions are ranging from intelligent search engines [3] to various intelligent data analytics methods [4]. The industry is going through a massive replacement of legacy systems such as Oracle/ Taleo and IBM/BrassRing [5]. Talent recruiting is the priority feature for start-ups as mentioned in youngest Chinese unicorns survey. Attracting top talent and building a corporate culture are strategic priorities for high start-ups [6]. Industries and firms that seeks to attain competitive human resource services using communication and information retrieval technologies rely on the most important strategy known as E-HRM [7]. And it is necessary essential to consider local idiosyncrasies and adequate recruiting tools [8]. In the first phase of AI; automation has already started and is playing into every aspect of daily life [9]. The efficient recruitment process has fuelled an additional interest in computerisation of all other industries procedures [10]. However, the difficulty lies in the selection of employees having the correct mixture of skills, enthusiasm and mature expertise possessing several challenges to AI due to its subjective nature [11,12].

According to CEO of IBM Ginni Rometty, human resources modelling methods that has traditionally been used losing success, requiring assistance from machine learning based methods. In IBM 30% of staff has been replaced with intelligent agents, which is helping its employees to identify advanced skills, training and education, job promotions criteria, and up-raises. Hirevue, the US company comes amongst the first few companies to develop interviewing technologies claims that it has enabled reliable and suitable objective indicators of candidates for future performance. “Facial expressions indicate certain emotions, behaviours and personality traits,” said Nathan Mondragon, Hirevue’s chief psychologist. This AI-driven video analytics framework analyses the language, ascent, facial expressions of candidates and their tone upon inquiring a set of identical job questions. This AI model is trained on 25,000 samples of facial and linguistic information compiled from previous interviews of those candidates, who were proved to be right/good at their jobs. Unilever UK is the first organization that used this tool in job interviews.

ARYA by LEFORCE uses AI for recruiting by organizing the data, learning, and retaining from it in almost every field including communication, software development, arts, culture & design, public relations, marketing advertising, copy writing, and journalism. It then delivers the relevant and candidate job intelligence directly into the industries pipeline, so to begin engaging with the right talent before other competitors even find that candidate [13]. ARYA also claims to predict even the employees suspecting to quit their recent jobs by analysing candidate’s current achievements, promotions, changing of their role within an organization, their social interests & discussions, and other open web platforms along with industries/ companies expected to be fit for new positions [14].

Life changing connections are only found with AI that transforms dispersed data into a story not only using machine learning but also incorporating the cutting-edge methods including natural language processing, deep learning, predictive analytics, proprietary algorithms, behavioural pattern analytics and neural networks. The deeper and smarter analysis tools have reduced the time of selection of potential candidates from 60% to 10% i.e. faster than humanly possible. Although far-reaching R&D has commenced regarding the E-HRM and talent recruitment, yet a significant gap remained in regards to E-HRM and its possible impact on potential start-ups [15]. Carrie Bermingham has done a study on investigating the impact that E-HRM has on start-ups with an emphasis on e-recruitment [16]. The data establishes the fact that start-ups are marginally utilising E-HRM as suitable practice in recruitments due to lack of expertise. In this context, AI-assisted recruiting tools can play a major rule in high potential start-ups, identifying and selecting the most desirable candidates. AI with recent innovation of deep learning is still in its infancy stage, meaning most of the AI systems in all industries are still in the learning phase and HR AI might not be 100% accurate but once it gets matured and properly trained on big datasets, it will assist HR discipline in a highly significant way.

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2019R1A2C1010786). This study was also supported by the BK21 Plus project (SW Human Resource Development Program for Supporting Smart Life) funded by the Ministry of Education, School of Computer Science and Engineering, Kyungpook National University, Korea (21A20131600005).

  1. Upadhyay AK, Khandelwal K (2018) Applying artificial intelligence: implications for recruitment. Strategic HR Review. Link:
  2. Sekhri A, Cheema DJ (2019) The new era of HRM: AI reinventing HRM functions. International Journal of Scientific Research and Review 7. Link:
  3. Raub M (2018) Bots, bias and big data: artificial intelligence, algorithmic bias and disparate impact liability in hiring practices. Ark L Rev 71: 529. Link:
  4. Palshikar GK, Srivastava R, Pawar S, Hingmire S, Jain A, et al. (2019) Analytics-Led talent acquisition for improving efficiency and effectiveness. in Advances in Analytics and Applications ed: Springer 141-160. Link:
  5. Kankaanpää I, Tiihonen P, Ahonen J, Koskinen J, Tilus T, et al.  (2007) Legacy system evolution-A comparative study of modernisation and replacement initiation factors. In Proceedings of the 9th International Conference on Enterprise Information Systems (ICEIS 2007) . Link:
  6. Earle HA (2003) Building a workplace of choice: Using the work environment to attract and retain top talent. Journal of facilities management 2: 244-257. Link:
  7. Olivas-Lujan MR, Ramirez J, Zapata-Cantu L (2007) e-HRM in Mexico: adapting innovations for global competitiveness. International Journal of Manpower 28: 418-434. Link:
  8. Barman A, Potsangbam C (2018) Marriage of Human Resource to Data Science: A Narrative. International Journal of Management & Organizational Studies 7. Link:
  9. Black JS, van Esch P (2020) AI-enabled recruiting: What is it and how should a manager use it?. Business Horizons 63: 215-226.  Link:
  10. Nawaz N (2019) How far have we come with the study of artificial intelligence for recruitment process. Int J Sci Technol Res 8: 488-493. Link:
  11. Girisha M, Nagendrababu K (2020) Challenges and Issues of E-HRM Practices in India. Our Heritage 68:  10. Link:
  12. Adam AK (2020) Modern Challenges of Human Resource Management Practice in Job Placement and Recruitment Within Organisations in the African Continent. Journal of Human Resource Management 8: 69-75. Link:
  13. Leoforce AB (2020) Intelligence-driven talent acquisition. Link:
  14. Heilweil R (2019) Artificial intelligence will help determine if you get your next job. Link:
  15. Škudienė V, Vezeliene G, Stangej O  (2020) Transforming human resource management: innovative e-HRM value creation for multinational companies," in Innovation Management, ed: Edward Elgar Publishing. Link:
  16. Bermingham C (2018) An investigation of e-HRM and erecruitment in HPSUs in Ireland (Recommendations for best practice). Dublin Business School.
© 2020 Farooq SS, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.