Artificial Intelligence in Talent Sourcing: Benefits and Challenges

The U.S. Bureau of Labor Statistics reported that 4 million people quit their jobs voluntarily in February 2023. Two of the biggest problems that organizations have right now are managing their attrition rate and talent sourcing. As more employees quit, organizations need to spend money, time, and effort in filling empty positions, and this cycle is often never-ending.

Talent sourcing is the practice of identifying, screening, interviewing, and hiring the right employee from a vast talent pool to fill a particular position. Identifying and hiring the right person is such a challenge right now that many organizations prefer outsourcing talent acquisition instead of trying to do it themselves.

With Artificial Intelligence (AI) making its mark in every industry possible, talent management experts are also exploring the idea of using AI to make talent sourcing more efficient, affordable, and effective. They believe that AI can effectively target some of the pain points of sourcing talent and make the process easier. Potential Benefits of AI in Talent Sourcing

The following could be some of the potential benefits of AI in talent sourcing - 

1. Accurate job posting

Sometimes, finding the right talent pool could be a challenge for the talent acquisition team. AI can be moderated to identify the right talent pool, analyze the most effective form of job advertisement, and post at a time that gathers the most response. Outsourcing talent acquisition to AI may help bring better leads when it comes to filling a role.

2. Automate basic screening

Usually, when a recruiter is asked if there is a boring part of their job and, if yes, what it is, the most popular response is - the initial screening. After a job posting, the recruiter may receive hundreds of resumes, and screening them based on requirements can be extremely tiring and mundane. AI can do this work in a fraction of the time needed by human recruiters. The talent sourcing team needs just to provide the screening requirements and sit back and relax while AI takes over and shortlists the resumes that match the criteria provided.

3. Predictive analysis

Apart from just screening a resume for required criteria, an AI tool can go several steps further in predicting the potential employee’s future with this organization. Predictive analysis is a feature of AI based on deep learning. This technique analyzes millions of data points, including past employment history, human patterns, and future industry growth, to make predictions like how long the employee would stay with the organization, the potential ROI of choosing the hire, and so on. The possibility of AI is never-ending when it comes to talent sourcing.

4. Affordability

While AI tools can be quite expensive to invest in at the beginning, they can smoothly take over the tedious pieces of work of recruiters across multiple levels. This, in turn, can help save a significant amount of staffing costs. AI tools also help find out the most cost-effective candidate in the list of available new hires and help improve returns on investment.

 Challenges in Using AI in Talent Sourcing

 Listed below are two of the most common challenges that talent sourcing teams face in using AI

1. Over-dependence on a growing technology

Outsourcing talent acquisition comes with the challenge of depending on the technology that is still being researched and growing. It has always taken human beings years to trust anything that’s non-human, and this is the same with AI. Trusting AI with hiring decisions may take some more time, and till then, organizations will need human expertise to cross-check and approve AI decisions.

2. AI-bias

When AI makes decisions based on its algorithms, the algorithms are created and approved by humans. Making minute changes to these algorithms may completely disintegrate the talent sourcing process. As a result, it is always important to ensure the AI algorithm is unbiased and free of intentional and unintentional errors.

AI makes decisions based on years of past data. Let us assume a company has never had female leaders in the past, and the AI is sourcing leads for a CXO position. The software may consciously choose male candidates over female candidates simply based on past data. This is a bias that can affect the quality of hiring and encourage sexism.

 Conclusion

Artificial Intelligence is definitely an amazing possibility to make talent sourcing more effective and efficient. However, it is also true that this newer technology is growing by the day, and it may take a slightly longer time to let it take over the sourcing process completely.

Till then, outsourcing talent acquisition to brands like InfoPro Learning can help organizations tweak their existing process and create a system that helps hire the best candidates quickly and confidently.