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Significance of Artificial Intelligence is Tremendously Increasing in Recruiting Process

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Significance of Artificial Intelligence is Tremendously Increasing in Recruiting Process
Artificial Intelligence (AI) and Machine Learning (MI) have become trending in recent discussions with business leaders about HR and recruiting associated technology plans for the coming year. It is obvious to say that the expectations of AI are increasing day by day. It is also apparent that while many are excited to AI due to the trendiness or coolness factor, a growing number of business leaders are now excited in how AI-powered capabilities can enhance the effectiveness and outcomes of their hiring attempts.

In this blog, we are highlighting some of the effective areas where applying AI is creating an impact and supporting to solve actual difficulties in talent acquisition. Most talent acquisition leaders are working in a recruitment environment that is more chaotic. While plenty of hiring data drifting around in enterprise HR systems, it is a big challenge for businesses to obtain valuable information from this data to support in recruiting decision-making and eventually better hiring.

AI Role in Talent Acquisition
Artificial intelligence making constant inroads into talent acquisition, it is now feasible to access this data. Most exercises in this area normally start with developments in regular and repetitive recruiting tasks like screening and scheduling automation and then advancing into more intelligence-based tasks like applicant engagement as well as forecasts to support with recruiting decision-making.

Below are the recruiting tasks that are generally automated using AI and machine learning to execute regular functions or augment human-centric skills.

Applicant sourcing:
surfacing eligible applicants from internal & external talent pools for the present vacancies.

Applicant screening:
evaluating applicant profiles and deciding their fit for a job opening.

Profile improvement:
automatically sourcing further information on a candidate from publicly accessible data over the web.

Personalised evaluations:
tailored solutions that adjust to each applicants’ abilities and skills.

Applicant matching:
recognising and assessing the most effective active or passive applicants for an open position based on their relevant experience, skills, or other specified criteria.

Programmatic job advertising:
automated distribution of job and budget optimisation that depends on past data and performance in the real-time campaign.

Chatbots:
conversational UI for applicants or prospects for Q&A, pre-screening, scheduling, and more.

Interview self-scheduling:
scheduling logistics automation, enhance hiring velocity with instant, real-time updates & confirmations, and enhance applicant experience by giving scheduling flexibility.

Here are a few areas in the recruiting process where AI and machine learning are creating an impact.

Applicant Engagement
AI-powered chatbots can support to create a compelling applicant experience by improving engagement and providing notifications to keep applicants updated on their status of the application.

Lessening bias with AI Recruiting
Insensible bias is possibly one of the most basic andhard-to-overcome obstacles of quality recruiting. With decision-making inspired by machine learning insights and algorithms, AI recruiting can assist in eliminating such biases, producing a more sensible and fair hiring process.

Predictive Models
Data-driven insights which are powered by AI-based recruiting technology– during various stages of the hiring process can empower stakeholders to make hiring decisions that are fair and maximise the possibility of success for the applicant as well as the company.

Fewer Errors with AI Recruiting
The functions that are automated with AI and machine learning are also less likely for human error and hence more chance for enhancing the overall improvement of the hiring process. Over time, with AI recruiting, organisations and recruiters can spend more time with applicants and less time doing repetitious tasks, eventually leading to greater productivity and lesser cost per hire.