With hiring volume up this year, recruiters are investigating new AI recruiting innovations to efficiently and creatively manage their increased workflow.
The eagerness for bigger and better tools has led to this rise in AI in recruiting: the application of artificial intelligence such as machine learning, natural language processing, and sentiment analysis to the recruitment function.
The interest towards adopting AI in recruiting is similar to why it’s becoming popular everywhere else – to automate or streamline parts of the workflow, especially time-consuming, repetitive tasks that were previously difficult or impossible to do.
Recruiting software that uses AI technology is presenting new opportunities for doing things differently. Here are 5 intriguing AI recruiting innovations.
1. Helps you write better job postings
A CareerBuilder survey of job candidates found a bad job posting is one of the top reasons candidates get a negative impression of a company. That’s especially unfortunate given how most companies seem to treat job postings like an afterthought.
Even when employers have the best intentions, their job postings might be turning off certain candidates from applying. For example, research has found that using too many “masculine-type” words (e.g., ambitious, dominate) in your job description may dissuade female candidates from applying.
To help you write better job postings and attract a more diverse talent pool, one of the best AI recruiting innovations can conduct sentiment analysis on job descriptions to identify potentially biased language and suggest alternatives.
Using AI to help companies create more appealing job descriptions makes recruiting more innovative by tackling the age-old problem of attracting more diverse and better fit candidates.
2. Let’s you cast a wider sourcing net
The second AI recruiting innovation can find passive candidates online by learning what the job requirements are from a job posting and then finding digital footprints such as social profiles, work portfolios, and even comments to find candidate matches.
This is the type of sourcing that a talented recruiter is already skilled at but with AI, you can do at a far greater scale and speed – finding hundreds of potential candidates in moments versus the days or weeks it would take to find them manually.
Using AI for external sourcing makes recruiting more innovative because it can find candidates that you may have previously overlooked using sources you might not have considered.
3. Mines your existing resume database
Glen Cathey calls it the biggest mistake in corporate recruiting: the failure to mine your existing resume database to find previous candidates for current reqs.
Similar to external sourcing, the third AI recruiting innovation analyses your job description and then searches your existing ATS database to find candidates who have applied to your company in the past who fit the requirements of a current job opening.
Using AI for internal sourcing makes recruiting more innovative because it automates candidate mining, which eliminating the need for recruiters to come up with long and complicated Boolean or keyword searches to conduct a resume search manually.
4. Speeds up your resume screening
Industry stats report that for every 100 applicants a job posting receives, about 75% get eliminated at the resume screening stage.
No wonder manually reviewing resumes when the majority end up in the rejected pile feels like a major waste of time.
The fourth AI recruiting innovation automates resume screening by analysing your existing resume database to learn what the qualifications of existing, successful employees are and then applies that knowledge instantly screen, grade, and rank new candidates.
Using AI to automate your screening makes recruiting more innovative because it reduces time to fill without sacrificing quality of hire. In fact, AI for resume screening has the potential to increase quality of hire because every resume can be objectively screened preventing candidates from falling through the cracks.
5. Reduces unconscious bias
Bias in hiring gets a lot of attention these days and for good reason. Research has found that resumes with white-sounding names receive 30 percent more interviews than identical resumes with the names changed to black-sounding ones.
The fifth AI recruiting innovation can reduce unconscious bias in two ways. First, by attracting, sourcing, and screening candidates using objective, data-based practices.
Second, the AI can be programmed to ignore demographic information such as gender, race, and age that can influence human decision making.
It can even be programmed to ignore details such as the names of schools attended and zip codes, that can be proxies for race and socioeconomic status.
Using AI to reduce unconscious bias makes recruiting more innovative because it uses technology to help solve a common problem that humans aren’t capable of eliminating on their own.
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