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How Companies Can Leverage AI Recruiting to Increase Representation in Hiring

A range of approaches to designing and utilizing AI can actually help diversity hiring.

Bias has always been an inherent part of job recruitment.

The collective weight, and oppression, of bias in the workplace is enormous—which is why the current push to eliminate bias in recruiting marks such a positive change. But it’s no simple task, and it's far from over.

Despite advancements in equity and technology in the 21st century, bias in recruiting remains a huge issue—including bias within artificial intelligence (AI) tools, whose usage is soaring in workplaces across the country. Today, some 46% of executives say they plan to use AI tools in their recruiting processes.

“From a practicality standpoint, whether it’s a large or small company, open roles often receive hundreds or even thousands of applicants,” said Rebecca Harris, director of Diversity, Equity, Inclusion & Belonging at Enspira. “It’s often about budget and efficiency. You can hire 20 recruiters to handle those requisitions, or hire five and then leverage tech to enhance the scope and reach of that smaller team.”

“Artificial intelligence and algorithmic decision-making tools have great potential to improve our lives, including the area of employment,” says Charlotte Burrows, chair of the U.S. Equal Employment Opportunity Commission (EEOC).

But to harness their power, companies must understand that AI tools don’t magically remove bias in recruiting. “The EEOC is keenly aware that these tools may mask and perpetuate bias or create new discriminatory barriers to jobs. We must work to ensure these new technologies do not become a high-tech pathway to discrimination,”Burrows warns.


Unconscious bias — when a person unknowingly has a positive or negative disposition towards an individual or a group — is deeply ingrained within the human psyche. 

This unconscious bias can be simple and pervasive right from the very get-go of the hiring process. A study analyzing the impact of gender on hiring revealed that 79% of applicants with a male name were deemed “worthy of hire,” versus only 49% of those with a female’s name. Another study published in the American Economic Review found that resumes with white-sounding names received 50% more calls for interviews than identical resumes with black-sounding names.


Will computers be the sole arbiters of whether you’re hired in the future? That’s unlikely — but they’ll definitely help.

“Most companies… are unlikely to abandon face-to-face selection procedures,” a recent report on automation from Deloitte states. “In such cases, technology can be used to support these procedures, saving time and costs and generating and evaluating additional data.”

AI programs are already being used within talent recruitment to streamline the hiring process, find the best candidates, and increase diversity. Applicant tracking systems provide a degree of automation that allows recruiters to spend less time parsing through online applications and more time interacting with prospective candidates.


Companies can improve their workplace culture by implementing intentional hiring practices that mitigate bias and increase diversity.

Enspira uses a five-step recruitment process that will increasingly utilize AI as a supplemental tool to reduce bias and improve diversity hiring in the future. Here’s how:

  1. Review Job Description. “Language is so critical, and can quickly introduce bias,” Harris said. She uses tools like Textio to ensure listings have gender-neutral language and scan job descriptions to ensure that requirements don’t inadvertently exclude individuals with disabilities.
  2. Assemble a Diversity, Equity, Inclusivity and Belonging Hiring Team. Do you have broad—visible and non-visible—diversity within your recruiting team? “If you do, your team is going to go out with that broad lens and broad network — and that’s the recipe for diversity, equity and inclusion,” Harris says. Companies can assess their data on, say, how many women or people of color applied, to ensure bias is not cutting underrepresented groups out of the hiring process.
  3. Cast a Wide Net.  “Where are you posting? If you’re going to the same network, and offering the same job rewards, you’re always going to get the same candidates,” Harris says. Look to establish relationships with diversity-focused organizations or schools like HBCUs (historically Black colleges & universities) or HSIs (Hispanic-serving institutions).
  4. Assemble Diverse Candidate Slates.  AI talent-sourcing platforms like     Plum, Eightfold, and Pymetrics can help identify soft skills, which are innate tendencies and behaviors that measure potential and can help employers make unbiased hiring decisions. 
  5. Standardize the Interview Process. “Equity means everyone goes through the same process, and the same evaluation,” Harris says.

“Tech has certainly made applying to jobs more accessible for more people in some respects,” Harris says. “Phone apps and online job listings make applications more accessible. And candidates can leverage tech, for instance by pulling in a LinkedIn profile’s data to save time on multiple applications.” 


Currently, AI recruitment tools are not federally regulated, but likely will be in the future. In 2020, Illinois became the first state to regulate AI use with its Artificial Intelligence Video Interview act, which stipulates that companies must notify applicants if AI is analyzing video interviews, and provide them with information about how that AI system works. New York City recently passed a bill requiring annual bias audits for hiring vendors that useAI-powered recruitment tools. And in 2021, the European Union proposed strict rules for AI use that could be a benchmark for future regulation.

The key takeaway here? As recently noted in Enspira’s white paper, Human Led, AI Assisted: Uniting Artificial and Human Intelligence to Combat Bias In Hiring:

Despite the advantages of AI, understanding that artificial intelligence is merely a tool that should not be used on its own, is key to ethical use. AI technology must be paired with a humanistic lens.

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