We’ve always believed that hiring the right talent is the cornerstone of business success. But in today’s fast-paced, digital-first world, traditional hiring methods, even those using what used to be considered the latest and greatest technologies, are being pushed for even more change. All of us in the recruiting business know what its like to sift through hundreds—sometimes thousands—of resumes, to chase down candidates, schedule interviews, and manage the countless communications involved in the hiring process to keep the right candidates engaged. Recruiting teams and hiring managers have been pushed to the limit for at least the last 5 years, exasperated by the ease with which candidates can apply for jobs. More work. Fewer hires. More hiring mistakes than most companies like.   

The promise we’re hearing is that AI will allow us to reshape the hiring landscape – new tools that will deliver faster, fairer, and more efficient methods of recruiting, evaluating candidates, ultimately better hiring decisions. But how exactly will that happen?  What are the challenges that will come when we start relying more and more on technologies, algorithms etc. to drive the hiring process?   

We’re writing this blog to describe AI tools we know are already in play in the business of recruiting and hiring plus what we believe will be the tools most likely to revolutionize how and who we hire.  We are seeing a lot of opportunities for break thrus, but there are also some risks or shortcomings in an AI enabled process that we are paying attention to.  We wanted to lay out these pluses and minuses for our readers who, rightfully so, are approaching this AI thing with both optimism and fear.  You can decide if its time to let AI cook in your work environment or keep it under watchful eye!

Resume Screening: From Hours to Seconds

One of the most time-consuming components of the recruiting process is resume screening. With the candidate’s ability to respond to a job posting just a click away, the number of resumes that recruiters see and are expected to review during the sourcing process has significantly expanded over the last decade.  If you’re a hiring manager, new to the resume review process, its easy to get overwhelmed by the sheer volume of resumes that come your way.  And let’s face it, it’s virtually impossible to give each resume the careful review the candidate’s submitting the resume are deserved.      

AI has definitely made a dent in the resume review step of the hiring process.  AI-powered APPLICANT TRACKING SYSTEMS (ATS) can automatically scan and ran resumes based on keywords, experience, skills, and more. Many of these systems pull their own key words from a job description and automatically pull candidates from a database or the web, flagging the best fits for screening.  AI has made a big dent in the time it takes for recruiters to identify the best candidates – in minutes not hours.

Using AI for resume screening……..

• Saves large amounts of recruiter time
• Reduces the number of candidates that need to be put thru the more labor intensive steps in candidate screening and evaluation   
• Is able to handle a high volume of applicants without slowing down the process

There are also some downsides of using AI to screen resumes…

• The reliance on the content of a resume to invite candidates into the hiring process.  This reliance not only can filter out great candidates who aren’t tailoring their resumes to job postings, but screens in the candidates who are who, in many cases, are not the best candidates for the job.    
• It invites the risk of reinforcing selection biases based on bots trained to focus on tangible data like work history, instead of other types of data that might better predict future performance.   There are many jobs where a candidate’s work style, personal qualities, are more important to hiring success than actual skills and experience.  These candidates are easily passed by as our candidates coming with non traditional profiles.  We worry that this process will deliver a level of discrimination that will disadvantage certain groups of candidates, particularly for the entry level jobs that provide opportunities for skill development.        

Can AI be developed to select candidates for talent in addition to skills and experience?  We think it can…but not there yet.       

Chatbots and Candidate Engagement – Who am I talking to anyway?

AI-driven chatbots can now handle everything from answering FAQs to scheduling interviews. Our team is not yet using these kind of bots ourselves, preferring a more human touch, but are being told by those who have deployed them that they provide a smooth, responsive candidate experience.  We need to be convinced that these bots can actually improve the candidate’s experience and are concerned that they might not be the right venues for keeping the best candidates engaged.

Why does candidate engagement matter?  In a competitive talent market, a slow or unresponsive hiring process, will result in disengagement from top candidates.  Robotic or canned responses, on the other hand might do even more harm.  We’ll see how communication bots used in the right way and at the right time can streamline the hiring process without doing damage to the quality of candidate’s hired.  

Video Interviews –Can AI see things we can’t!

Yes, we’re using AI tools to analyze video interview, assessing a candidate/s answers against a preferred candidate profile.  We haven’t yet tried this application of AI, but being told that on the horizon is AI software that assesses facial expressions, tone of voice, and word choices. In the near future we hope to be demoing AI software that will evaluate a candidate’s soft skills and predict job performance based on the behavioral data collected during a structured interview.

What we like most about the video interview tools we are currently using is that they incent us to standardize our interviews, to minimize the impact of unconscious biases, and the the time management benefits we get from making early assessments of a candidate’s  soft skills – before we get too far into the evaluation process. 

What we don’t like about these tools is the ongoing wonderment about the accuracy of the assessments, the risks of making superficial assessments based either on body language or speech patterns.  We’re looking for the scoring algorithmns to be made transparent before we feel comfortable embracing automatic assessments based on video interviews.   

Skills Assessment and Behavioral Matching – Hiring for Talent!

Rather than focusing solely on resumes, AI tools can evaluate actual skills through online skills assessments.  This technology allows us to match candidates to roles based on capabilities, not just job titles or canned job descriptions.  We like this feature because it enables a more inclusive and forward-looking approach to hiring which is something we regularly advocate for.

More specifically, the ability to identify candidates based on their talent profile, not just their actual work experience is a really good way to deal with career changers, candidates coming from non traditional work backgrounds, or when recruiting for roles where there aren’t enough experienced candidates in the marketplace to keep up with the demand, and you need to select candidates based on their transferable skills or raw talent.  

Predictive Analytics – Faster, Better, Easier Hiring Decisions

For larger,enterprise level companies, who hire a lot of people into the same or similar roles, AI can be a really good resource for comparing past hiring data with performance post hire.  This capability helps companies make data-informed decisions about the link between hiring criteria and results that has the potential of renewing stakeholder trust in structured hiring processes.  For example, if you’re trying to fill a role requiring a unique combination of hard and soft skills, a company can develop a set of predictive analytics to create a preferred candidate profile and then guide the recruiting and candidate selection process at each step up to the hiring decision.

The downside is that while these capabilities are great at reducing risk, they aren’t good at identifying the exceptions to the rule.  They are also capabilities not available to most small to sized companies.       

Ethical and Legal Considerations: A summary!

While AI has the promise of delivering game changing efficiencies, it also raises three serious ethical and legal concerns….

• Bias and Discrimination: If your AI agent is trained using biased data as its input, it will replicate and even amplify existing inequalities in hiring.
• Transparency: Candidates may not understand how they’re being evaluated if AI decisions are opaque, breaking down the trust in the process in further than what it is today. 
• Efficiency.  Will the drive to move faster, drive out the human touch in the hiring process to the detriment of both the candidate and the employer .

Our Thoughts on BEST PRACTICES for AI and Hiring!

We’re not prepared to get detailed about best practices, but,  in the big picture,  for any company to use AI responsibly, we think its important to…..

• Regularly review your AI tools for glimpses of bias or unfairness.  What candidates tend to screened out or screened in by your AI agent?    
• Use AI to support—not replace—human judgment.  Don’t under resource the human side of your recruiting team just yet . Let them do what they do best…to review and insert human judgement into the hiring process.  
• Pay attention to communications.  Let candidates know how you are using AI – what it is doing for the process, what it is not doing to the decision
• Pay attention to how real candidates are reacting to your new AI facilitated journey.  Regularly ask candidates about how they experienced your hiring process and if the AI insertions helped or got in the way of a great candidate experience.  Have you architected a process that delivers the human touch when it’s needed.

Final Thoughts

AI has the potential to dramatically improve the hiring process—to make it a faster, fairer process, better aligned with your unique organizational goals. But it’s not a magic solution. Human oversight, ethical considerations, and continuous evaluation are critical to making AI work for both companies and candidates.  We continue to believe that the best hiring strategies combine all the strengths of technology/AI with the unique and highly personal connections that only humans can provide.

We’d love to hear from you?

Have you used AI in your hiring process? What’s worked—and what hasn’t?