That’s especially harsh because rejected offers and early resignations can completely derail your talent management planning and even affect your revenue. What’s worse, it seems like it’s an HR occupational hazard that is mostly unavoidable. In other words, you make offers that get rejected and people leave shortly after you hire them because they don’t feel comfortable.
While that’s a reality you’ll have to face at some point or another, you should aim to reduce the times it happens to a minimum. Fortunately, you can rely on Artificial Intelligence (AI) to help you out.
The Problem with Traditional Selection
Traditionally, job searches go like this: Your c level contact list HR department puts out a job offer, receives applications, interviews candidates, and decides which one is the most qualified among them. Recruiters often make that final decision based on their own assessment of what the role entails and what the candidate can offer. Thus, they analyze the candidates’ experience, expertise, and overall fit with the company.
The thing is, that analysis is mostly subjective. While recruiters typically get help from experts in different fields to analyze a candidate’s role-specific skills, they end up making the decision based on a lot of factors, some of which might include personal biases. This can lead to your company hiring someone who isn’t precisely the best match for your needs. That, in turn, can lead to the candidate rejecting the offer or starting work only to leave after a short while.
How AI Can Help
Using AI can boost your recruitment main features to look for in an email marketing tool efforts by informing recruiters during their assessments. The idea is fairly simple: Using machine learning models, you can use past hiring data to analyze multiple factors that amount to a total score, indicating how reliable a recruiter’s assessment actually is.
Such models should aim to be predictive, as they can uncover hidden patterns and behaviors that indicate whether a particular candidate is perfect for the role or not. Naturally, this isn’t the only way in which AI can help recruiters during selection and beyond. Some of the applications AI has for human resources management include:
- Quickly assessing and filtering a large number of résumés based on specified criteria
- Making suggestions on matching talent with your specific needs
- Interpreting data of past hiring cycles to uncover improvement opportunities
- Offering insights on how to improve the onboarding process
While all of that might seem too good to be true, it’s actually what AI can offer your company right now. Indeed, at BairesDev, we employ a proprietary AI-powered approach to swiftly assemble top-tier engineering teams. This process is tailored to meet highly specific criteria, which may include expertise, past performance, and client preferences. With an influx of over 1 million applications each year, we are well-equipped to find the best fits.
The Challenges of Using AI for Recruitment
As transformational as they may be, AI chile business directory solutions for recruitment will only provide good outcomes as long as you address the potential risks surrounding their implementation. The most notable ones include:
- You need a highly trained AI solution. Without the proper training, the algorithm will offer mistaken suggestions and biased insights that may end up hurting your business rather than helping it.