How new-age data analytics is revolutionising the recruitment and hiring segment
10.12.2020 Filed in: AI
This is where AI-powered technologies come in with the potential to revamp the entire recruitment process. Accessible and economical ML-driven hiring systems can conveniently replace conventional hiring processes. Due to the software, company employees can be relieved of the routine mundane tasks and be delegated instead to high-skilled roles; hiring would be more transparent and devoid of any biases, and the AI entities can give personalised attention to each job-seeker. Even post-hiring, much of the onboarding formalities and training can be managed effectively by AI.
Alongside AI, agile and nimble workplaces have become the order of the day in the employment sphere. However, scouting the right talent and integrating them within the workplace environment takes a good amount of time. The entire process can be expedited through data analytics as machine learning can be used on Big Data to make forecasts about the talent requirements that are likely to arise within the organisation, based on the trends in the past and the fluctuating demands for the company’s products.
Benefits of AI and ML in Recruitment There are innumerable advantages attached to opting for AI over an ordinary recruitment team. With the introduction of AI, companies can easily lower the costs involved in maintaining a recruitment team. The highly automated screening procedures select quality candidates that in turn will help the organization grow and retain better personnel – a factor that is otherwise overlooked in the conventional recruitment process.
Employing AI and ML automates the whole recruitment process and helps eliminate the probability of human errors. Automation increases efficiency and improves the performance of other departments of the company. The traditional recruitment process tends to be very costly. Several teams are often needed for the purpose of hiring people in a company. But with the help of AI and ML, the unnecessary costs can be done away with and the various stages of hiring can all be conducted on a single dedicated platform.
Additionally, if the company engages in a lot of contract work, then AI can be used for analysing the project plan and predicting the kinds, numbers, ratio and skills of workers that may be required for the purpose. The scope of AI and ML cannot be undermined by the capabilities of current systems.
Current Scenario In talent acquisition and onboarding is where AI has made long strides. It is extensively being used in job portals, such as an AI recruitment chatbot or AI-driven candidate screening process. Most search and discovery solutions only find candidates based on the same keywords used when writing the job description. But AI and ML make the process more skill-centric and less job title-centric.
As Natural Language Processing (NLP) and Virtual Reality (VR) become a reality and gain popularity, the whole process of onboarding and training new recruits also becomes highly automated. Instead of traditional human training and paper-based SOPs, recruits can be empowered with AI-based assistants and VR or AR support tech to wade them through essential information and their responsibilities.
AI and ML have already replaced quite many profiles and roles. About 72% MNCs have made AI-based HR technology a part of their organisational thread and many others are planning on making the move. The technology is expected to make a profit of $37 Billion by 2021. Already 72% of Multinationals companies have adapted the AI-based HR technology and many more are planning to move. Reports have shown that approximately 41% of recruiters use AI-based processes, as it’s helping them save almost 80% of their hiring time.
Summing Up To leverage the best of AI and ML, it’s essential that the administration within companies welcomes technology-adoption unequivocally. Its penetration cannot be avoided; hence, the only prudent move would be to adopt it and adapt to it.
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