Article: Artificial intelligence - A game changer in the recruitment ecosystem

Technology

Artificial intelligence - A game changer in the recruitment ecosystem

Lets have a look at the role of AI in retaining the right talent to build sustainable businesses.
Artificial intelligence - A game changer in the recruitment ecosystem

In the current job market where millions of new candidates enter the workforce every year, organisations are desperately working towards building an effective recruitment process. This involves finding the right talent and limiting the risk of a bad hire and the aftermath that follows. The task of getting the right talent on-board in a cost and time effective manner looks like a distant dream to most. The exponential increase in the number of applicant’s, little or unstandardized signals about their job suitability and a large amount of unstructured data make it worse.

A typical recruitment process today revolves around shortlisting a candidate through his/her resume, interaction with a couple of line managers and pre-hiring checks. Unfortunately, these interactions do not offer any quantifiable indicators of the skills and competencies of a candidate or his/her ability to do a specific job. Most recruiters continue to rely on conventional hiring methods that are largely un-scalable, non-objective and ineffective. Artificial intelligence can change all of this – it can help you understand the skills of a person better and build quantitative models of what skills are needed for what jobs. The huge amount of applications and data, which are a challenge today, become a boon in the world of data-driven artificial intelligence.

A simply stated classical approach to AI led hiring would want the organisations to extract data for all employees it hired in the previous year and find who performed well or not. Based on this, they will build a predictive model of success based on parameters like educational qualification, experience, stated skills. Now, they can apply these models on every new applicant to find his/her propensity to succeed and reduce low performers. They can also interpret these models to guide their staff better on what to care during screening/interview. These insights allow organisations to move beyond subjective hiring, reduce hiring mistakes and recruit talent based on evidence.

Unfortunately, sometimes the above approach is wanting because the resume parameters do not tell us enough. Among two candidates who claim to have java skills, one may really know it and the other might be faking it or is ignorant about his/her skills. This is where skill assessments come into play. Interestingly AI helps here too! With machines nowadays being able to do several sorts of intelligent tasks like driving and understanding images, they can also help assess skills as good as humans do. There are sophisticated evaluation tools available today which offer automatic evaluation of computer programming skills, spoken English and interpersonal skills which are often overlooked but critical in several fields.

In a recent case, a sample of 90,000 US college students took an automated programming assessment. The tool identified 16% candidates who have the right thought process but do not pass test cases. These are rejected by conventional tools not based on AI. On the other hand, it found 20% super good programmers who write maintainable and efficient code. These programmers are the dream of any IT product company! A regular recruitment process with no assessments or use of conventional tools would have missed these candidates.

Many organisations have today just begun to invest into assessments and predictive analytics. Looking at the benefits associated with data driven decision making, the time is not far when Artificial Intelligence will seep into every aspect of recruitment to improve overall efficiency. Performance is not the only aspect where organisations can benefit from data analytics but it can also cater to the other aspects of the recruitment cycle like retention. The vast amount of unstructured data like resignation patterns, common features of exiting employees, job satisfaction levels etc. can generate powerful insights and help build a better workforce. While these issues were earlier unquantifiable and unstructured, adopting technology can change the way organisations can benefit from this data.

While learning and assessment is a relatively new domain which is seeing the AI invasion, structuring the vast amount of data can benefit not just organisations but also the talent ecosystem on the whole. Investing in AI for skill measurement and matching is the key for organisations to identify and retain the right talent to build sustainable businesses.

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Topics: Technology, HR Technology

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