According to recent data, the adoption of Artificial Intelligence (AI) technologies has increased by 70% in the last five years and it is thought that global spending in AI will increase from $85 billion in 2021 to over $204 billion in 20251. In an era when technology is reshaping industries and ways of working, AI is steadily transforming human resource (HR) management and talent acquisition. From the tedious task of going through countless resumes to finding the best talent, the integration of AI has brought about a new age of efficiency and precision in the recruitment and selection processes. This blog is the first of a short series, where we will explore how AI is altering the hiring landscape, offering a glimpse into the numerous ways in which it is reshaping how organisations find, engage and retain top talent.
AI can facilitate each stage of the recruitment and talent management processes – here, we focus on how AI can help organisations find the right candidates for the job by supporting employer branding efforts and facilitating candidates screening.
With regard to outreach, different AI tools can use existing job descriptions to automatically create a shortlist of appropriate candidates either from internal talent pools or talent profiles that can be found online2. Furthermore, AI can enhance employee attraction by creating more accurate job postings3. For instance, software programmes like Textio use an AI technology, which adopts text-mining techniques to determine the attractiveness and, thereafter, the success of job postings4. Research has also indicated that AI can be used to determine if job ads are more likely to attract more male or female applicants and thus create more inclusive job postings through gender-neutral wording to reach a wider pool of potential candidates. Lastly, interview studies have indicated that HR professionals believe that AI can enhance company attractiveness5.
Moving on to the screening of candidates, one of the most commonly cited advantages of AI in the context of recruitment and selection is that it can help to quickly review and analyse large numbers of resumes and applications. By automating repetitive and time-consuming tasks like candidate screening, HR professionals can have more time to focus on strategic decisions5. In addition to improving the efficiency of the hiring process, AI can eliminate human biases in the initial screening as it assesses applicants on the basis of objective criteria and their qualifications. It can thus reduce the likelihood of discrimination. Building upon this, AI can match candidate profiles to job descriptions and can also use historical data to determine a candidates’ potential and organisational fit, which can lead to more accurate hiring decisions. Hence, AI’s ability to objectively process large volumes of data and provide data-driven insights makes it a valuable tool for improving the candidate screening process.
In the next two blogs we’ll explore the use of AI in the context of talent assessment and retention as well as the ethical considerations that organisations need to take into account in order to capitalise on the opportunities that AI offers.
References
1Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A. and Truong, L., 2023. Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human Resource Management Review, 33(1), p.100899.
2 Oswal, N., Khaleeli, M. and Alarmoti, A., 2020. Recruitment in the Era of Industry 4.0: use of Artificial Intelligence in Recruitment and its impact. PalArch’s Journal of Archaeology of Egypt/Egyptology, 17(8), pp.39-47.
3 Schmid, K., and Raveendhran, R., 2022. Where AI Can – and Can’t – Help Talent Management. Harvard Business Review.
4 Hunkenschroer, A.L. and Luetge, C., 2022. Ethics of AI-enabled recruiting and selection: A review and research agenda. Journal of Business Ethics, 178(4), pp.977-1007.
5 Ore, O. and Sposato, M., 2022. Opportunities and risks of artificial intelligence in recruitment and selection. International Journal of Organizational Analysis, 30(6), pp.1771-1782.
