Technology infused with artificial intelligence (AI) is starting to become ubiquitous, even in enterprise recruiting. From our email inboxes to the smartphone apps we use daily, AI algorithms drive choices and user experiences. The modern-day enterprise must do everything it can to stay ahead of the curve, so it should come as no surprise that AI is leading that charge.
Researchers estimate that 80% of companies now use AI as part of their HR workflows. Recruiting is one of the central pillars of any HR department. Given the subjective nature of talent acquisition, HR departments have been slow to transition to AI-driven processes. However, as the three examples listed below will show, AI technology is at an inflection point. It’s bringing immense value to enterprise recruiting.
Removing Unconscious Biases
Human beings are a collection of biases. It’s almost impossible to prevent them from creeping into our judgment. Recruiters face an uphill task here. Their unconscious biases might result in the company missing out on attracting top-tier talent. They could also unintentionally discriminate against candidates from certain backgrounds.
It can even be argued that simply by writing job descriptions, recruiters are necessarily introducing self-fulfilling subjectivity to talent evaluation. Research has shown that a company’s choice of words in their job descriptions acts as a filter. For instance, descriptions that imply a “work hard/play hard” culture attract candidate pools that are disproportionately male.
Similarly, job titles such as “hacker” or “guru” tend to attract more male candidates. More neutral titles might be “engineer” or “developer.” Descriptions that excessively use superlatives are also likely to make women feel excluded. Lengthy “nice to have” requirements are also likely to filter out women. Women are less likely than men to apply for a position where they don’t fulfill all the criteria completely.
Tools such as the Gender Bias Decoder and Textio use NLP algorithms to analyze job descriptions and highlight possible biases. Additionally, AI can be used to detect unconscious recruiting biases. For instance, a recruiter might instinctively trust someone who attended the same university more than another qualified candidate. Someone who grew up in certain parts of the world might receive more consideration than someone with an unfamiliar background, and so on.
AI can remove these emotional biases and improve hiring standards. They can help companies strike a balance between human and machine-driven judgment. There’s no doubt that AI brings immense value to the table.
Leveraging AI to Improve Diversity, Inclusion, and Equity
Diverse workforces lead to better products in today’s global marketplace. Thanks to their digital presence, enterprises source customers from every corner of the planet. Localizing talent only limits a company’s ability to understand its customer’s needs.
Often, good candidates slip out of a company’s recruiting funnel because these candidates don’t come from traditional backgrounds. For instance, a company might have hired employees primarily from Ivy League schools in the past. That student population skews towards a certain demographic. The result is a workforce that represents the Ivy League demographic and excludes equally talented and capable people who don’t hail from the same backgrounds.
One frequently heard accusation against the use of AI is that it reduces human beings to mere data points. However, in enterprise recruiting, this can be turned into a useful feature if the algorithm is configured properly. Apart from removing biases in hiring, it also alerts companies to a much larger talent pool and different perspectives.
For example, Joonko is a service that helps companies use AI to source employees from diverse backgrounds and increase the inclusion of their workforce. Their algorithm reviews candidates who were once seriously considered for employment by participating companies. The software identifies ethnic backgrounds and genders from public data sets and then surfaces talent from underrepresented cohorts. The results appear in a dedicated feed in the recruiter’s applicant tracking systems.
Critically, AI nowadays has access to a widening array of data sources. For example, AI configured to hire software developers trained on historic employment patterns are likely to hire a white male from a Western country. More diverse data sets remove demographic information from consideration. This ensures that a person’s skills are all that matter when evaluating a good fit.
Recruiting and Hiring According to Tailored Attributes
Recruiters often worry about employee-to-company fit. Do the employee’s values match the company’s culture? Will a prospective hire fit into the company culture? Are they likely to be left behind? Will the new hire help the company maintain its edge in the market? Analyzing the answers to these questions is, of course, a subjective process.
Thankfully, AI can ease this process immensely. What if, for example, an algorithm could look at the existing workforce and create a database of qualities of people who tend to succeed at the firm? For instance, being self-driven is a common requirement for many smaller companies. Such people might not fit well within an enterprise environment.
A search of the company’s employee database might reveal successful employees in that enterprise that work well within structured environments as opposed to an unstructured one. Cultural fit is preserved by evaluating equally qualified candidates along these lines.
Tools such as PredictiveHire make it easier for recruiters to analyze their workforce in this manner. In addition, AI tools can also highlight possible diversity issues within the workforce. Recruiters can spot trends and nip them in the bud before they become problematic.
Enabling a Commitment to Increased Progress
Of course, AI isn’t a perfect solution for everything, and enterprise recruiting is no exception. However, with the right balance of human and machine-led judgment, enterprise recruiting is changing. Companies are hiring and retaining better workforces. A resilient and fair marketplace is the result. Any recruiter’s highest value should be merit and AI-enhanced tools can help make that happen.
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