IT is facing significant talent shortages, and new HR AI talent recruiting systems are touted as being able to help. How do these systems work, and where to apply them?

Mary E. Shacklett, President of Transworld Data

March 22, 2022

7 Min Read
robot arm selecting a cube representing an employee
Zoonar GmbH via Alamy Stock

IT is facing significant talent shortages, and new human resources AI talent recruiting systems are touted as being able to help. How do these systems work, and are they effective?

The purpose of artificial intelligence hiring and talent scouting systems is to reduce the amount of work that HR or IT conducts in the activities of talent seeking, candidate evaluation and hiring.

For example, if you’re looking for a senior project manager, it's not uncommon to receive 300 or 400 resumes. All these candidates are applying because they believe they have the experience and the requisite skills to do the job you want to fill. However, unless you have an effective way of narrowing the funnel to a much-reduced number of candidates, you will have a long and tedious recruiting process that could last weeks or even months before it culminates in a hire.

AI can help with upfront resume evaluations because of its ability to rapidly analyze and sift through resumes, identifying the key experiences and job skills you are looking for. AI can even use machine learning (ML) to further improve its accuracy and its performance as it gains its own experience while reviewing data.

How does AI do this? It programmatically looks for the specific job skills, experiences, and other characteristics of your ideal candidate that you have already input into the AI processing engine, and then identifies a smaller pool of candidates who fit your criteria and whom you can look at more closely.

AI can even go beyond skills and experience evaluations in its analyses. It can evaluate social media posts and voice tones of candidates for personality traits and interests that could influence your decision on whom might be the best “fit” for your IT team.

Here are three ways AI recruiting systems can address IT leaders’ biggest talent issues:

1. Filling job openings

In 2021, nearly half of all companies said they were having trouble finding skilled workers, and Gartner opined that “IT executives see the talent shortage as the most significant adoption barrier to 64% of emerging technologies, compared with just 4% in 2020.”

HR AI can help in talent acquisition because of its sheer ability to evaluate hundreds and even thousands of resumes from a diversity of sources. The AI can quickly winnow down the funnel of applicants to a more manageable group of resumes you can begin to evaluate.

At the same time, AI is non-thinking. It makes decisions based upon the criteria that you have given it. So, if you want a data analyst with at least five years’ experience, the AI is going to pore through resumes and find out who those applicants are. If you don't like the group of candidates that the

AI has identified, you can alter your search algorithm and run the AI again.

2. Underutilizing and losing staff

The 2022 job market is a job seeker’s market. This makes it highly competitive to fill positions, and equally challenging to retain your own staff.

The most likely people to leave a company are highly skilled employees who are in high demand (e.g., IT). Employees who feel they are underutilized and who want to advance their careers, and employees who are looking for work that can more easily balance with their personal lives, are also more likely to leave.

It’s also common knowledge that IT employees change jobs often, and that IT departments don't do a great job retaining them for the long haul.

HR AI can help prevent attrition if you provide it with internal employee and departmental data that it can assess your employees, their talents and their needs based upon the search criteria that you give it.

For instance, you can build a corporate employee database that goes beyond IT, and that lists all the relevant skills and work experiences that employees across a broad spectrum of the company possess. Using this method, you might identify an employee who is working in accounting, but who has an IT background, enjoys data analytics, and wants to explore a career change. Or you could identify a junior member of IT who is a strong communicator and can connect with end users in the business. One aerospace company did this and found that individuals with liberal arts degrees (not degrees in IT or computer science) were uniquely qualified for business analyst positions -- but the company wouldn't have thought to look there without the help of AI for soft skills searches.

An HR AI system can also assess corporate employee climate surveys to see how employees feel about the company and about work -- and how satisfied they are with their work-life balance. If you see IT teams scoring low, you can take proactive steps to improve the culture -- and you could improve employee retention.

3. Finding strong team players and leaders

IT is one of the most challenging areas when it comes to finding strong team players and leaders. This is because IT can be fiercely competitive. Individuals are continuously benchmarking their technical prowess against that of their peers.

HR AI systems can help by identifying those individuals with inherent leadership and team-building skills.

Often, these individuals aren’t always your top technical performers, so there need to be additional checkpoints to ensure that they have sufficient IT chops to be able to interact with top performers.

CIOs usually identify IT leaders through direct daily observation. But HR AI can also help because it can identify individuals at earlier stages of their IT careers who have the potential to become strong leaders in the future.

Do AI Recruiting Systems Have an Achilles Heel?

The Achilles heel of HR AI systems is that they do only what you tell them to do. If you give AI information that is limited, it will perform analytics that are limited. For example, a software company has a history of hiring employees who are predominantly male, and it wants to use AI to evaluate its history of successful employment and look for similar candidates. It’s likely that the company will miss out on candidates who might be female or persons of color because the company doesn’t have a history of hiring employees from these groups.

The bias usually comes from the data because the data isn’t representative of the characteristics you are trying to hire for in a broader marketplace. This places your company at a disadvantage when it comes to finding and evaluating candidates, and you're likely to miss out on good hires.

The second Achilles heel of AI is that it isn't human. Yes, AI can be programmed to perform sentiment analysis from the tones of individuals’ voices, but can it replace the connections (or lack thereof) that interviewers and staff members experience when they meet job candidates face to face?

Takeaways for Recruiting with AI

AI recruiting systems can be enormously helpful when it comes to narrowing down a field of applicants into a funnel of best choices that IT wants to look at more closely. At the end of the day, however, it is the human connections that interviewers and staff feel with candidates, in addition to the skills that candidates bring, that really matter.

HR AI can also be actively used to identify internal employees who can have the potential to grow into more demanding positions. However, for IT and HR to capitalize on this, they must commit to the upfront work of cataloguing employee skills, interests, and backgrounds so the AI can use this data to identify potential fits for new projects and work. This is an area where companies historically lag. But it can be a real differentiator for retaining and developing talent that the company already has within its own four walls.

What to Read Next:

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About the Author(s)

Mary E. Shacklett

President of Transworld Data

Mary E. Shacklett is an internationally recognized technology commentator and President of Transworld Data, a marketing and technology services firm. Prior to founding her own company, she was Vice President of Product Research and Software Development for Summit Information Systems, a computer software company; and Vice President of Strategic Planning and Technology at FSI International, a multinational manufacturer in the semiconductor industry.

Mary has business experience in Europe, Japan, and the Pacific Rim. She has a BS degree from the University of Wisconsin and an MA from the University of Southern California, where she taught for several years. She is listed in Who's Who Worldwide and in Who's Who in the Computer Industry.

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