AI in Remote Tech Recruitment: Do’s and Don’ts

Finding the right tech candidate requires recruitment teams to evaluate and test skills more thoroughly. And HR teams are now changing their evaluation strategies by implementing AI technologies. This way, they can hire more efficiently, reduce time-consuming tasks, and shortlist candidates to those who could be a great fit. 

As remote work is taking a significant role in today’s corporate world, most companies all over the world have started to hire and manage a virtual workforce. Remote IT professionals are in high demand across several industries. 

However, the tech industry is one of the hardest to recruit talent from. An Indeed survey found that 9 in 10 HR professionals said that finding and hiring technical talent is challenging. 

The quantity of candidates applying for a job is not the problem; the quality is. And recruitment teams’ major challenge is screening candidates and identifying those qualified enough to fulfill a role.  

A talent acquisition survey revealed that while 46% of leaders struggle with attracting strong candidates, 52% believe that the most difficult aspect of the entire recruitment process is identifying suitable candidates from a large applicant pool.  

So, how can teams and HR professionals tackle this problem? By implementing artificial intelligence solutions on their remote tech recruitment processes. 

How is AI Used in Remote Tech Recruitment? 

Just as social media platforms such as Instagram, Tik Tok, and Twitter changed the game of brand marketing in every industry, artificial intelligence is transforming HR and recruitment as teams can use this technology to automate their processes.

AI is being used in talent acquisition processes to help teams quickly and effectively shortlist ideal candidates. Overall, this technology focuses on streamlining some parts of the recruitment that tend to be repetitive.

When automatization processes are designed correctly, they can help both the recruiter and the candidates to develop a better experience. For instance, AI helps recruiters reduce repetitive and administrative tasks like manual searching, reviewing a high volume of CVs, scheduling, etc., allowing them to focus on more meaningful parts of the recruitment process such as interviews.  

On the other side of the coin, AI helps candidates to have a more customized and efficient application process. They experience a streamlined and organized process and get faster responses.

However, the success of AI in the remote tech recruitment process depends on how you use this technology. For example, when talent acquisitions processes rely too much on AI, it can affect the candidate experience negatively, ignoring those who might be a great fit but didn’t have specific keywords on their CV.  

Furthermore, AI recruitment has proven in some cases to have a bias against specific target audiences. Like the case of Amazon, where machine-learning specialists realized that their new recruitment engine did not like women.

Do’s and Don’ts of AI in Tech Recruitment 

AI is the present and future for many industries. HR teams across the world will continue implementing it in their recruitment strategies. However, learning and identifying the dos and don’ts of AI in your recruitment process will provide better results and help you hire the candidates you need for your company. 

1.   Do: Automate Resume Screening

One of the biggest advantages of AI in tech recruitment is automating resume screening. Most HR teams, even those working in small companies, receive thousands of applications. Reading one by one and along with cover letters makes the recruitment process slower and sometimes ineffective.

Manually screening CVs is one of the most time-consuming tasks in recruitment. According to Ideal. evaluating and shortlisting candidates takes 23 hours of a recruiter’s time. And this is just for a single hire.

With AI, you can screen resumes faster, reducing the time spent on repetitive tasks. You’ll have all the necessary data you need to know which candidates are worth interviewing and which are not.   

Another perk of screening through this technology is that you get rid of the unconscious bias some recruiters might have when evaluating candidates. 

2.  Don’t: Focus Only on Mandatory Skills

One of the dangers of AI in tech recruitment is losing talented candidates just because they didn’t have what the “ideal’’ resume should have.

Let’s say you need a React developer. The mandatory skills are those that are non-negotiable; the ones a candidate needs to perform successfully. In this case, it would be skills such as knowledge in HTML, CSS, JSX, and JavaScript, among others. On the other hand, the preferred skills are the ones you wish they had but are not as important as the mandatory ones.

In every profession, other skills are not deal-breakers. If you add this giant list of mandatory skills, the chances are that few candidates will be eligible for the role.

A talented and experienced React developer might not be chosen just because they didn’t add specific keywords or because they didn’t have that ‘’mandatory’’ skill.

Before you start using AI to screen resumes, make sure you decide which skills are mandatory and which skills are preferred with your team. From here, you can rank candidates based on how many of these preferred skills they have. 

3.  Do: Analyze Your Target Audience – Ideal Candidates

Analyzing your target audience in simpler terms means knowing who your ideal candidate is. A simple example to illustrate this is when you have a new product in your company, the best way to sell it is to know your buyer persona, right? With tech recruitment, it happens the same.

Conducting a market insights report is helpful when you have a small or unqualified talent pool. This might happen because you’re focused on hiring local candidates instead of remote candidates. Or it may happen because you don’t have an in-depth understanding of who your ideal candidate is, and therefore the AI search you’re conducting isn’t clear on what type of candidate to look for.

Before starting researching for candidates, evaluate the available candidate market. Then set your hiring expectations and discuss them with your team. When you have finished this process, you can start a new AI search based on this report.  

4.  Don’t: Automate Interviews

Because of the increase in remote work, companies are now using different tools to manage their virtual teams. The HR areas have an easier way of recruiting because of AI and all the different platforms they have to conduct interviews or onboarding processes, providing candidates and new employees with a great experience. In this case, while AI helps recruiters identify candidates easily, it doesn’t always work with interviews.

A candidate might have a great CV but might not have the right personality traits for the job. Or might not fit into the company’s culture. And this is what interviews are all about, in evaluating and testing a candidate’s skills and knowledge and knowing them on a more personal level. Automating interviews takes all this away. 

Additionally, it can negatively impact a candidate’s experience affecting your company’s reputation. Candidates might feel the entire interview process was dehumanizing and that they weren’t evaluated fairly. 

5.  Do: Use Hidden Filters

Imagine you want to hire remote developers. However, you need them to speak fluent English. Using AI can help you narrow your search into specific states and countries where developers speak fluent English, making the hiring process faster.

When you refine your search, you have a greater chance of finding qualified talent. One of the benefits of using AI in tech recruitment is adapting it and adjusting it to your needs. Each tool has its filters, so you can discover those who work best for you, and that will help you deliver powerful results.

As the previous example, you can conduct your candidate research based on specific locations that interest you for different reasons. It can be language, living costs, or time zones. This will help you have a talent pool that adapts to your specific needs. Another filter you can use is industry-related. You can seek candidates in specific industries and exclude those unwanted industries that do not interest you. 

6.  Don’t: Lose the Human Touch

AI can be a double-edged sword when it comes to tech recruitment. On the one hand, you could save a lot of time by avoiding tasks that take a lot of time. But on the other hand, you could miss great talent and give candidates a negative experience.

Using AI effectively consists mostly in evaluating what processes make sense to have automatized and which don’t.  If you think that automatizing the entire recruitment process will help you save time and provide great candidates, you’re wrong.

While there are great tools to identify body/facial language, it’s not the same as having a regular video interview and talking to the person.

Another negative aspect of only relying entirely on AI recruitment is the fact that AI empathy can’t replace human empathy. Keeping in mind that often, people in most industries, not only in the tech industry, are in a vulnerable position when seeking jobs. And machines don’t respect or express empathy for job candidates.

Too much automation as a consequence, besides making you lose potential candidates that can provide a lot of value to your team, makes candidates lose interest as there is no human interaction involved.

A Final Note

AI is gaining popularity in the remote tech recruitment industry as it helps HR teams to streamline and automate specific aspects of the hiring process. They can avoid reviewing hundreds of CVs every day to focus on other tasks. Additionally, candidates may experience an organized and clean recruitment process.

However, despite all the benefits, AI also has challenges that organizations need to learn how to tackle. Challenges like analyzing data, losing potential talent, dehumanizing the entire recruitment process, or the fact that HR teams might not have their ideal candidate persona make it harder for  AI tools to provide the right candidates.

Before using AI in tech recruitment, remember to keep in mind these do’s and don’ts to have a better experience that allows you to hire the best candidates.

FAQ

Are AI Tools Biased?

Yes, what happened to Amazon is a clear example of how even AI technology can learn human biases.
In recruitment, AI could eliminate unconscious bias by ignoring age, gender, and race information. However, as this technology is trained to find patterns, it can replicate similar behaviors. This is why it’s important to constantly monitor any potential patterns to ensure that all candidates are equally evaluated and that there are no preferences regarding certain genders, ages, or cultural backgrounds. 

How Effective is Using AI for Tech Recruitment?

Very effective. AI not only benefits recruitment teams by helping them reduce time in repetitive tasks but it also helps them automate processes that positively impact a candidate’s experience. For example, scheduling meetings or replying fast are all things that can be automated and could enhance the hiring process of candidates, improving a company’s reputation.
Some other benefits are:
– It helps recruiters identify talented candidates.
– Reaches candidates in a meaningful way.
– It makes the hiring process faster and simpler.
– Maximizes a recruiter’s productivity
– Provides powerful metrics.

What are Great AI Tools for Tech Recruitment?

5 of the best AI recruitment tools that can help HR teams to source, screen, and hire talented tech candidates are:
Paradox: This application uses machine learning to interact with candidates through a conventional chatbot called Olivia. With Olivia, applicants get answers to all the questions they might have during the hiring process. 
AmazingHire: It’s a powerful sourcing tool that helps recruiters analyze the professional backgrounds of technical candidates, collecting data across over 70 different sources.
Eightfold: Consists in a talent intelligence platform that reviews thousands of applicants’ profiles in seconds, providing recruitment times with an instant pipeline of qualified candidates.
Textio: Textio uses big data and machine learning to help recruiters optimize their brand’s language to decrease the bias implicit in anyones’ language. 
Loxo: Is a recruitment CRM that helps recruiters find the best talent fast. They have an updated database with more than 530 million people.


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