It seems that any news about how artificial intelligence (AI) is changing recruitment is closely followed by criticism of how biased it can be. Let’s take a look at why AI is being applied in recruitment and key growth areas, as well as strategies for preventing bias and building trust in this new technology.
Why is AI used in recruiting?
The New York Times offers a refreshingly simple look into AI in recruitment from a candidate’s perspective. In the article “Résumé-Writing Tips to Help You Get Past the A.I. Gatekeepers,” the Times describes succinctly, and with just a touch of world-weariness, AI’s role in today’s recruitment landscape:
To wade through this ever-rising tide of résumés, human resources departments are increasingly turning to artificial intelligence systems to pluck out the candidates deemed to be good fits.So-called predictive hiring tools evaluate résumés by finding keywords related to categories like skills, experience and education, and weighting them according to the job requirements and any other factors the hiring company has specified. The system may weigh applicants who have worked at certain companies more positively. It may infer how old a skill seems to be from where it appears in a job history.
The Wall Street Journal is a bit more sanguine, setting the stage by noting that “[a] chronic shortage of workers has more employers turning to artificial intelligence to supercharge recruiting efforts, seeking an edge in an increasingly pitched battle to fill job openings.” The Journal enthuses:
Artificial-intelligence capabilities, like conversational AI software, can speed up the early back-and-forth emails, texts and other communications with applicants and quickly get strong candidates in front of recruiters. Other AI-enabled tools are being used to accelerate the employee onboarding process, getting new hires oriented, trained and set up with computers, business apps and corporate email accounts.
AI-assisted recruiting is catching on like wildfire because it works.The Journal also reports that roughly 80% of 400 human resources and other corporate officials surveyed this year by information-technology trade group CompTIA said they expect AI to have a moderate to significant impact on HR and recruiting in the year ahead. According to the survey, most companies are already piloting or actively using AI in candidate screening, onboarding, competency assessment and career planning.
Companies recruiting workers in highly competitive industries such as trucking, healthcare, and warehousing and logistics report increases of up to 40% and more in the number of hires they are able to make per quarter, reducing the time from application to payroll from several weeks or months to about one week.
Key areas where AI can impact recruitment
Artificial intelligence is making significant inroads at every step of the recruitment process, improving efficiencies, speeding time to hire and lowering costs.
Building a talent pool creates a group of “warm leads,” candidates who are already sold on your company and welcome opportunities from it. Cultivating a talent pool can reduce important metrics including time to hire and cost to hire, as improving overall candidate quality.
The win: Having a talent pool gives you a pre-qualified group of potential candidates.
- Candidate sourcing: With an estimated 50,000 job boards globally, placing recruitment ads can be a guessing game. AI-powered job advertising enables employers to analyze the efficacy of job postings to see which boards deliver the most qualified candidates, per position.AI can also improve the quality of hires, with robotic process automation (RPA) to search for, compile and rank suitable candidates. RPA can identify and consider factors that may not be obvious to the recruiter. For example, RPA is capable of comparing a candidate’s resume on different job sites and matching that information with data gathered from social networks. In this way companies can be apprised of inconsistencies in a candidate’s presentation.With AI fueling candidate sourcing, new efficiencies can drive down recruiting costs as advertising spend is optimized, driving down costs.
- Job to candidate matching: Often a candidate for one job may be better suited for another. This holds true in both active recruiting, when a candidate applies for Job A and may be better qualified for Job B, and passive recruiting, in which previous applicants that applied and were rejected can be identified for future open positions. AI can be used to build position profiles to which candidates can be matched.
- Candidate screening: After candidates have applied, RPA can be further applied to screen them by assessing and rank-ordering their qualifications. Applicant tracking systems (ATS) use AI to quickly screen resumes for specific keywords related to the job requirements. Natural language processing (NLP) technology is often employed to assess resumes on word choice and content to help determine which candidates should be shortlisted.
- Candidate experience: AI-powered recruiting chatbots and assistants provide an easy and efficient way to gather basic information from candidates, to better inform human recruiters prior to their conversations with them. Application details and screening questions can be collected by chatbots and saved to the job application, eliminating the long process of transactional information gathering via email, calls or texting. By being respectful of the candidate’s time, chatbot-assisted recruiting can have a positive impact on the experience.
- Onboarding: RPA can help automate background checks by automating queries to all manner of databases used in the process and generate offer letters or flag exceptions. Hiring processes can also be automated, speeding the time to hire while greatly reducing the need for humans to be managing them. Once hired, chatbots can again be useful in onboarding, answering newcomers’ general questions and providing them with information or resources based on current onboarding programs. These questions can range from culture and policies to employee benefits such as health insurance, vacation, sick days and 401(k) matching contributions.
- Job ad content: AI-powered analysis of job postings can significantly improve their quality by optimizing word choice and reducing bias. Job postings can be analyzed for gender neutrality, removing unconscious bias and gender-coded language from job ads. Here, AI can yield more high-quality, diverse and inclusive applications, in addition to improving search engine visibility. Check out Joveo’s blog on this topic, “Sourcing a More Diverse Workforce: 5 Ways to Improve Inclusivity.”
Providing transparency in AI-assisted recruiting
AI is routinely used to screen resumes and, by extension, assess and rank-order their candidates. Such scoring is also an opportunity for employers to build goodwill, as prescribed in The Wall Street Journal:
When people apply for a job, they will see a list of the hiring criteria, such as degree requirements, specific skills and the number of years of experience, so that they know precisely what a company is looking for. Then, if the applicant is rejected, the AI will present them with another list, showing where they didn’t meet the criteria or compared unfavorably to other applicants—the reasoning behind the decision.
In other words, we should show people very clearly what factors are used to judge them, just as we show people the ingredients that go into their food.
By providing reason codes for rejections, just as banks are required to provide to applicants reason(s) why they were rejected for mortgages or loans, companies can build goodwill by bringing transparency to today’s AI-fueled recruitment world.
You can get started with AI-powered recruitment advertising by requesting a demo of Joveo solutions today. Keep coming back to the Joveo blog for more fresh, original thought-provoking content. And follow us on Twitter and LinkedIn, where we’re always working to help you get the most out of your recruitment advertising.