Benefits And Use Cases Of AI Recruiting Software in 2023

The top AI recruiting solutions empower HR and talent acquisition teams to accelerate their efforts by removing tiresome chores through intelligent automation and allowing recruiting teams to concentrate on the most strategic aspects of their hiring process.

At Trenzle, we like to compare artificial intelligence to an exo-skeleton that enables humans to be smarter and more productive. We firmly believe that it will be decades or more before AI actually replaces people. As the new technology is really just slightly smarter software that can automate more of the jobs you probably don’t want to do, there’s really no reason to be terrified of it.

The HR and recruiting teams should be aware of some significant caveats to these use cases and hazards, therefore please also read the problems below this section. Listed below are a few use cases where AI recruiting tools can be useful:

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• Screening: The most effective AI recruiting technologies aid in prospect screening, but depending on the vendor, they do so in various ways (see below bullets). Generally, chatbots that will ask the candidate a series of questions come to mind when we think of AI interviews. To correctly screen the possible employee and respond to any questions they may have regarding the position, the AI is utilised to interpret the answers the candidate gives (as well as any queries they may have).

• Video Interviews: Platforms for video interviews are beginning to use AI to try and grasp some of the most important traits of an applicant. These platforms, in the beginning, can comprehend the answers job searchers provide to a specific query and assess how that meets with your hiring requirements. Also, there are technologies that can assess a job applicant’s confidence, extroversion, etc.

• Tech Screening: Engineers who might not have the résumé you’re searching for but who might be interesting hires can be thoroughly screened using automated tech evaluations. These platforms employ AI to assess a candidate’s performance on questions about their knowledge of several languages and critical skills like pair programming or test-driven development.

• Sourcing: AI is excellent for finding talent, and it has been used in this use case for a while. The fundamental concept is that artificial intelligence (AI) can evaluate a job description, locate pertinent individuals using various databases (such as your ATS/CRM or the public internet), and then produce a qualified list of probable applications. Even your sourcing can be automated using this technology, and multi-stage outreach can be initiated by SMS and email.

• Scheduling: Scheduling candidates is never easy, particularly when trying to coordinate several corporate calendars for an on-site. The correct interview scheduling software improves the candidate experience (no lost balls, female prospects don’t interview with all guys, etc.) and relieves a lot of the administrative burden from your hiring staff.

• ATS Re-Engagement: Your application tracking system (ATS) is brimming with excellent candidates who were late applicants, silver medalists, or who weren’t a good fit for a particular position at a certain moment but would be fantastic for a new req. Millions or thousands of records would take a human a very long time to sort through, and most application tracking systems aren’t very good at finding previous records. In order to re-engage prior applicants, AI can look at your open req and search your database for pertinent candidates.

• Referrals: AI recruiting tools are excellent for boosting referrals as well. Similar to the ATS re-engagement use case, this one uses your employees’ networks as the database rather than the ATS. The AI analyses your job posting, scans the networks of your employees, and then suggests candidates for your hiring team. All of this is possible without a recruiter having to do anything.

• Career Site Conversion: The majority of visitors to your career site don’t submit an application for a job. Job searchers can ask inquiries about benefits, open opportunities, and other topics using a chatbot on your career website. This increases the number of qualified prospects who enter your applicant tracking system.

Pitfalls You Need To Be Aware Of

Artificial intelligence recruiting tools include drawbacks and risks just like any other new technology. Keep in mind that artificial intelligence is an adjunct to human beings, not a substitute. Hence, we do not need to be concerned about losing our employment, but we must also keep in mind that we are still in the people industry and that interpersonal communication is still crucial.

• Candidate Experience: We all want to be respected, at the end of the day. The anxiety of the hiring process intensifies this urge. Don’t completely automate the applicant contact points. Job seekers will become disinterested because they are aware that they aren’t receiving any special treatment. Spend some time talking to prospective hires to see how they feel about the various steps in your hiring process and when you’ve gone too far.

• Set Expectations: Whether it be through Google searches or an automatic response to a straightforward query from a service rep bot, we are all accustomed to interacting with robots and AI. In general, we’re satisfied with this encounter. But, we must be aware of how a process will develop and that we can contact a person when necessary. I’m fine with entering my information to check my credit card pre-qualification. But if the situation worsens and no one is present, I can formally say that my experience was negative.

• Training the AI: A data set is used to teach AI to predict results. For you to benefit, you either possess this data set, or your vendor must require a dataset pertinent to your business. This training can be time-consuming at times. Know how this procedure will affect your use case and business. For a Natural Language Processing engine, for instance, training can be carried out automatically, but is frequently still overseen by people who check the data sets and ensure that the engine recognises the words where it makes sense to do so. This would inevitably take more time and raise concerns about the handling of your applicant data.

• AI Bias: You will have a recruitment process that discriminates against women if you provide the AI a dataset that is biassed against women. As the new Apple Card discovered, this actually happens more frequently than you may think. Always have humans double-check the reasoning behind any AI-based choices, especially when introducing new technology.

• Humans Needed: Consider the recommendations provided by AI recruiting tools. If you receive five applicants from your sourcing tool, it’s likely that at least one of them won’t be a fantastic fit. When it comes to talent acquisition teams utilising AI, humans often need to make the final judgement.