In 2017, AI and automation technologies were the major recruitment trends along with workplace diversity, talent relationship management and people analytics. This year, more changes are expected in the recruitment space along with the acceleration of known trends.
In the current job scenario, millions of new candidates are entering the workforce every year. So, organizations are increasingly focussed towards making the recruitment process effective with the right hire every time. This can help them overcome the aftermath that follows a bad hire, such as lower employee productivity.
Conventional hiring methods are non-objective, non-scalable and largely ineffective. To deal with an increasing number of applicants and the unstructured talent pool with poor mapping of candidates, hiring managers need to rely on artificial intelligence. AI-enabled hiring processes can eliminate human bias and help in making better recruitment decisions.
AI is likely to transform recruitment processes in these profound ways.
First is, The Emergence of Conversational Interface
A large number of applicants never hear back from recruitment managers. At the same time, several job positions remain unfulfilled. Inefficient recruitment tools and processes make it extremely hard for recruiters to track applicants and find right candidates who can work with motivation to achieve higher employee productivity.
As a large number of resumes are getting stuck in the corporate hiring pipeline, some of the recruiters have started using HRMS software with advanced AI algorithms. AI-based applicant tracking systems with conversational interface can help users track interactions between candidates and employers, and scale up their recruitment efforts even with limited resources.
HR chatbots can further prove useful in improving responsiveness. These AI-powered assistants can help employers hire new talent and assist applicants in seeking jobs as per their skills. Some of the popular recruitment assistants are Mya, JobBot, Jobo & EstherBot. While Jobo can search jobs for applicants depending upon their skill sets, JobBot uses AI to assess and rank candidates.
Secondly, Machine Learning
Recruiters don’t have enough time and resources to leverage their connections and benefit from massive networks. For instance, even when recruiters have 5, 000 plus LinkedIn connections, they can’t filter out suitable contacts easily based on requirements of different job profiles. This is where machine learning comes into play. Machine learning helps recruiters narrow the field of search and help recruiters focus on analysing candidate skills.
Going deeper, machine learning can also provide a broader view of workforce trends for specific job titles in particular industries. For instance, machine learning can give insights on the duration after which web developers start looking for better opportunities. Accordingly, recruiters can target specific candidates for effective hiring and higher ROI on recruitment activities with improved employee productivity.
Third is, Growth of Predictive Models
Predictive analysis is becoming quite popular among HR professionals, as it helps them benefit from human capital-based statistics. Companies can become more proactive in their hiring process, and generate algorithms from the latest workforce trends to predict the future needs of hiring.
With predictive analytics in recruitment, HR managers can fetch data from online sources like social media platforms to improve their recruitment marketing strategies. At the same time, predictive analytics implementation can help in evaluating third-party recruiting firms, job boards and other sources.
Even Google has implemented predictive models to reinvent and improve recruitment, leadership, employee productivity and retention. It has resulted in Google producing amazing results in terms of workforce productivity. On average, nearly $200,000 is generated in profit and $1 million in revenue each year by every Google employee.
The HR function at Google is dramatically different from others, and is known as “people operations”. All people management decisions at Google are driven by people analytics to define leadership characteristics and the role of managers.
What Lies Ahead
Artificial Intelligence for hiring and recruitment can help recruiters standardize their processes, and assess a candidate’s skills and ability objectively. Also, artificial intelligence technology can remove inherent biases prevalent in traditional processes of sourcing and selection.
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