How to use AI in recruitment

Author Kristine Angeltvedt, CEO of Nixa.io

There’s no doubt artificial intelligence and machine learning have accelerated during the last couple of years, and are now being embraced by recruitment agencies to reduce the risk of hiring bias. In response to the pandemic, companies have adopted technology to unprecedented levels, from video conferencing to project management and more. A McKinsey Global Survey has found that the pandemic accelerated the digitalisation of some business aspects by three-to four years. 

Technology is transforming how we work and it can help us make better choices when recruiting. While other industries have integrated technology into their everyday practices, HR has been a step behind. Change is afoot as the benefits of technology in recruitment are being recognised now. 

Why use technology in your recruitment process

This technology can help you hire more efficiently through screening without bias, creating shortlists of candidates who accurately match the job description and so much more. It can conduct sentiment analysis on job descriptions to ensure there’s no hidden bias in the language, manage conversations on websites and messages with chatbots, and evaluate employees’ lifetime performance

Technology really can help match the best candidates with a job from your pool. Using AI and machine learning can help streamline your recruitment process and improve the quality of your hires. 

AI doesn’t have biasesAI helps eliminate bias

This means your hiring process is becoming fairer. AI will ignore age, gender and race until it is trained to recognise them. The training will come from previous work in your recruitment process. AI can be continually monitored to watch for unconscious bias in its activity, so you’re much more likely to get a candidate who is right for the job rather than choosing someone based on other factors.  It is not perfect, but it’s constantly being improved to eradicate bias. 

Better matches

As we can collect more data about how candidates perform following their hire, we can ensure better matches. There is a vast amount of data that can be collected from candidates and employees, and used correctly means that the best people can be matched for a role. Better matches mean happy and productive employees and a reduction in turnover. Collecting data on employees’ performance will give you insight into the skills your teams need to do their jobs well. 

Save time

Menial tasks take up a lot of time which is where AI can step in. Screening candidates’ CVs is one task that can be quickly done with technology, and a time saver when around 75% of CVs submitted aren’t suitable for the job role. Candidates can be automatically put forward for assessments or scheduled for interviews. Screening CVs and shortlisting candidates is estimated to take a recruiter 23 hours, and that’s for a single hire. Your screening process has a big impact on your recruitment conversion rates, and tech can improve them further. 

Vodafone started using this tech back in 2017 to help with their recruitment processes and select the right candidates. Candidates had to submit videos of themselves answering a questionnaire. Computer algorithms assessed their suitability for a role based on facial cues and voice intonation, and those who passed this screening were put forward for interview. With thousands of CVs to review, AI really does help save time and money. 

Data collection

AI can be used at every step of the recruitment process, collecting data points from CVs, emails, videos and more. Vodafone collects around 25,000 data points from an employee video. The more data that can be collected, the better that the AI can be trained. You will need data to train the AI system and it will be an ongoing task as your organisation grows. The more data that can be fed to the system, the better your matches.  

The big picture

The ultimate test of AI and machine learning will be the savings, both in time and money. With recruiters freed up from menial tasks to focus on the things that really matter, such as detailed screening of shortlisted candidates and employee performance. 

When trained with the right data, AI can have a significant impact on your bottom line. Vodafone was able to reduce time-to-hire from 23 to 11 days in the early stages of AI adoption. It’s highly likely that this has been reduced further. Most importantly, candidate dropout rates were cut by 30 percent. 

It’s time to embrace AI and machine learning in your recruitment process to get the quality hires that you deserve. 

Author: Editorial Team

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