Find out how HackerEarth can boost your tech recruiting

Learn more

How AI Is Transforming The Talent Acquisition Process In Tech

Isabella is a recruiter at a multinational company with 1000+ employees. Her responsibility is to recruit the top talent—which she performs well by consistently looking for candidates that fit the company culture, collecting their information, reaching out to them, screening them, and finally interviewing them.


She carries out the entire process manually—leading her to invest much time in the manual tasks—resulting in disengaged candidates (because who likes to wait this long?).

If you are a recruiter just like Isabella, you’ll soon find yourself burnt out and left without achieving your recruitment goals. This is where artificial intelligence has got you covered. In 2023, AI will play a major role in shaping candidate recruitment and making the lives of recruiters easy.

In this article, we’ll help you understand how artificial intelligence is used in technical recruitment.

What is artificial intelligence?

According to Techopedia, artificial intelligence is the field of study in which computerized systems can learn, solve problems and autonomously achieve goals under varying conditions. Simply put, artificial intelligence is about training the computer or the bot to do tasks that humans do—by feeding more data.

So what does artificial intelligence in technical recruitment refer to? It means a relevant technology has been used in the hiring process. There are three basic tech models artificial intelligence uses: descriptive, predictive, and prescriptive.

  • Descriptive: It tells us about what’s happening
  • Predictive: It gives us an image of the future
  • Prescriptive: It tells us what we should do based on the insights and findings

With this technology in the recruitment software, HR teams can focus on more strategic tasks without burning themselves out with manual efforts like candidate sourcing and outreach campaigns. Because organizations want to accelerate their talent acquisition efforts at scale, they hire recruitment agencies to find the top tech talent. But, when AI recruitment software is employed at your organization, you won’t have to rely on these recruitment agencies entirely—saving up 15-25% of employees’ first-year salary.

How can AI be used in technical recruitment?

Here are 7 ways how artificial intelligence helps improve the technical recruitment processes and set the ongoing recruiting for success.

Candidate sourcing

Recruiters spend ample time identifying top talent across hundreds of sources and platforms to find the best possible matches based on the job description—from job portals to social media profiles, they source candidates from multiple channels which is a time-consuming process.

When a recruiter sources tech candidates via LinkedIn, here’s what their process looks like:

  • Searches for the candidate on the LinkedIn search bar with relevant keywords
  • Gets a list of candidates from the received results
  • Scans the LinkedIn profiles of candidates who match the job requirements
  • Reaches out to them via Inmail or LinkedIn DMs

Improved technical recruitment with recruitment software

Recruiters have to invest time searching and scanning each profile. The process is toilsome. On average, recruiters lose 14 hours per week completing such tasks manually. Clearly, using recruitment software tools that help with candidate sourcing is a much better option. These tools look for candidates matching the job requirements and conduct outreach campaigns.

💡Pro tip: Use tools like Fetcher and Recruitee

Candidate screening

In a traditional screening process, recruiters prepare and send assessments to candidates. Once the candidate submitted the assessment for review, the recruiter checked each assignment manually.

Imagine the time a recruiter has to invest if they were to screen 100 such assessments manually. If the recruiter screened 100 candidates, they had to review all the dedicated assignments.

With AI, role-based assessments chop recruiters’ time to half. Role-specific assessments are the way AI screens the candidates. Candidates take these tests to showcase their knowledge and skills.

HackerEarth’s Assessments help you evaluate the developers’ skills with advanced coding assessments—all you have to do is upload job descriptions, create coding test interviews and find the top developers with the auto-generated leaderboard. Also, you can create the coding test interview from the list of interview questions to simplify your process.

For example, Nirvana Solutions used HackerEarth’s Assessments for technical candidate screening and reduced their cost per hire by 25%.

Why this works: Before using the automated screening method, the company relied on manual screening of applications which was a time-consuming process and led the company to exhaust its resources. Now, Nirvana’s team takes 5 minutes to create automated assessments and around 30 minutes to create the assessment from scratch. After the candidates submit the test, recruiters analyze candidate reports for each candidate’s performance—helping them screen and identify the top talent within 10 minutes.

Posting jobs

If you google “job boards to attract diverse candidates”, you’ll find endless results. Earlier, the most common were and Indeed. But, with time, job boards have expanded allowing organizations to distribute their job listings and attract the right tech talent.

Unfortunately, mass distribution of your job listing isn’t possible when you are a one-person army. That’s where AI tools like GoHire help recruiters and organizations automate job posting across different job boards.

Also read: A Checklist For Writing Job Postings That Actually Work

Hiring remote workers

Gone are the days when companies hired candidates from the same location. Walk-in interviews have been replaced by video interviews—which has helped companies to hire candidates while sitting in the comfort of their homes.

Sidenote: If your company follows a hybrid or remote work model, AI amplifies your recruitment efforts.

For example, after screening the candidate with automated assessments, you move to the next stage of conducting a face-to-face interview—which is conducted using a video platform like Zoom and Google Meet.

These tools miss out on features that recruitment software possesses, making AI in recruitment more prominent.

Let’s say, after screening the candidates via HackerEarth’s Assessments, you can use FaceCode to invite the candidates to schedule interviews, conduct live coding interviews with a panel of 5 interviewers, and evaluate them based on automated interview summaries with AI-based behavioral insights.

Diversity hiring

Unconscious bias is one of the staggering norms in the tech industry. Because tech is a male-dominated industry, companies see them as the right candidate compared to women. A 2022 report by emphasizes the gender diversity of software engineers where women represent only 21% of the workforce in software engineering.

And this bias starts right at the beginning of the technical recruitment process. Recruiters analyze the candidates based on multiple factors like location, gender, and educational qualifications on reference by the company’s employees.

But when AI comes into play in the recruitment industry, you shift towards unbiased hiring. This Twitter thread by Diversity Council Australia shares how women feel confident about applying to tech roles when companies use AI recruitment software.

Diversity hiring helps in technical recruitment

Image Source

There are two ways in which AI recruitment software removes biases:

  • When you use AI to send assessments to the candidates, you test them based on their skills. Once they submit the assessment, you get a report of each candidate and how they performed—this analysis helps you screen them and move to the next stage. During this process, your recruiter won’t focus on the candidate’s resume, location, or gender. They’ll *only* focus on the candidate’s skills and how they performed the assessment reducing biases.
  • When interviewing candidates, robots can conduct face-to-face interviews. They analyze the candidate’s response based on the conversation, facial expressions, and a mix of natural language processing and body language analysis—which helps remove prejudice

Data collection

Imagine adding recruitment software that sorts data and saves the 5 hours that you’d have spent doing the work manually. You could focus on improvising your current recruitment strategy, in these 5 hours.

In a traditional setup, a recruiter would start by writing the job listing and sifting through inbound job applications to find the right fit.

In the modern setup, recruiters find candidates on LinkedIn to build the database. Before building this database, they have to brainstorm and answer questions like:

  • How can I find the ideal candidate on LinkedIn?
  • How to identify and shortlist the candidate for a specific yet complex set of skills?

Once you identify the answers to these questions, you start your search, collect data and build the candidate’s database to carry out the recruitment process further. But here’s the thing: sorting through multiple data points and collecting candidates’ data is a tedious process. Employing recruitment software that collects candidates’ data and analyzes it, candidate sourcing becomes much easier.

AI Recruitment software like Hiretual acts as a candidate data engine for your tech recruiting requirements—it centralizes all your talent management and helps you source across 750M+ profiles and actively rediscovers lost profiles.

Candidate onboarding

From sharing the resource documents based on their role to telling them about the salary processing, health insurance, and so on—you need to exchange a lot of information with the new hire once you onboard them.

No doubt you can rely on a single person assigned for helping in the onboarding process, but the time taken to onboard the new hire will take more time than expected impacting the credibility of the organization.

With AI employed to onboard new employees, you can simplify the overall technical recruitment process.

Seamless onboarding of new hires with chatbot

For instance, Unilever implemented artificial intelligence to onboard new employees. The company used Unabot, a natural language processing (NLP) bot to understand what employees need to know and fetch the information for them when asked. The AI acts as a forefront for questions employees have—from HR questions to department-specific questions like IT systems and allowances. Beyond this, it also answers questions like:

  • Where is the parking available?
  • What’s the timing for shuttle buses?
  • When are the annual salary reviews due to take place?

Basically, Unabot is the Alexa for Unilever—helping the company get rid of the back-and-forth of email and Slack messages to find and send resources when required.

Also read: Remote Hiring and Onboarding Tips for Technical Roles 

Get ready to transform your technical recruitment process with artificial intelligence…

No doubt why recruiters like Isabella constantly ask themselves, “how to recruit tech talent?”. When you carry out each recruitment task manually, you are compressing the space for productivity and efficiency. A simple way to get out of this situation is by employing an AI-based recruitment software in your organization that:

  • Increases pay transparency for employees
  • Enhances candidate experience with pre and post-hiring communication
  • Provides accurate assessments of diverse candidates and identifies the most qualified candidate
Hackerearth Subscribe

Get advanced recruiting insights delivered every month

Related reads

8 Top Tech Skills to Hire For in 2024
8 Top Tech Skills to Hire For in 2024

8 Top Tech Skills to Hire For in 2024

Hiring is hard — no doubt. Identifying the top technical skills that you should hire for is even harder. But we’ve got your…

How HackerEarth and Olibr are Reshaping Tech Talent Discovery
How HackerEarth and Olibr are Reshaping Tech Talent Discovery

How HackerEarth and Olibr are Reshaping Tech Talent Discovery

In the fast-paced tech world, finding the right talent is paramount. For years, HackerEarth has empowered tech recruiters to identify top talent through…

Subjective Match on HackerEarth Assessments: Make Technical Screening Smarter
Subjective Match on HackerEarth Assessments: Make Technical Screening Smarter

Subjective Match on HackerEarth Assessments: Make Technical Screening Smarter

In tech or coding assessments, subjective questions are open-ended questions that require the candidate to provide a more detailed or nuanced response than…

7 New HackerEarth Assessments Product Updates in 2023 You Should Know About
7 New HackerEarth Assessments Product Updates in 2023 You Should Know About

7 New HackerEarth Assessments Product Updates in 2023 You Should Know About

This year, as the industry went through a hiring freeze, we at HackerEarth took the time to elevate our product lineup so that…

AI Recruiting Software: Revolutionizing the Hiring Process
AI Recruiting Software: Revolutionizing the Hiring Process

AI Recruiting Software: Revolutionizing the Hiring Process

In today’s dynamic business landscape, organizations are constantly seeking ways to optimize their talent acquisition strategies to attract and retain top performers. The…

A Detailed Guide on Conducting Effective System Design Interviews
A Detailed Guide on Conducting Effective System Design Interviews

A Detailed Guide on Conducting Effective System Design Interviews

System design interviews are becoming increasingly popular, and important, as the digital systems we work with become more complex. The term ‘system’ here…

Hackerearth Subscribe

Get advanced recruiting insights delivered every month

View More

Top Products


Engage global developers through innovation

Hackerearth Hackathons Learn more


AI-driven advanced coding assessments

Hackerearth Assessments Learn more


Real-time code editor for effective coding interviews

Hackerearth FaceCode Learn more

L & D

Tailored learning paths for continuous assessments

Hackerearth Learning and Development Learn more