AI Recruiting Software: 11 Best AI Hiring Tools for 2024

In today's dynamic business landscape, organizations are constantly seeking ways to optimize their talent acquisition strategies to attract and retain top performers. The traditional way of hiring takes a lot of time because there are many manual tasks involved. Another problem is that when people judge candidates, it can be biased. These issues, along with others, make traditional hiring methods less effective.

Powered by cutting-edge machine learning algorithms, AI recruiting software is transforming the hiring process. These softwares are automating repetitive tasks, providing data-driven insights, and ensuring unbiased candidate selection.

In this article, we will delve uncover:

The transformative impact of AI recruiting software
How AI recruiting software can streamline your recruitment efforts

What is AI recruiting software?

AI recruiting software is an innovative technology designed to automate and optimize various aspects of the hiring process. It leverages machine learning algorithms and natural language processing to analyze and interpret vast amounts of data. Plus, you can automate the process of screening resumes, job descriptions, social media profiles, and more.

The benefits of AI recruiting software

AI recruiting software offers numerous benefits that can significantly improve your hiring process. It can automate tasks, analyze data, and provide insights. By leveraging AI, companies can identify the right candidates faster, reduce hiring costs, and improve overall talent acquisition outcomes. Let's delve into some of its key advantages:

Benefits of AI recruiting software

1. Enhanced efficiency

Think about the usual way companies hire new people – it often involves doing the same things over and over, taking up a lot of time. AI recruiting software is like a smart assistant for recruiters, automating these repetitive tasks. This automation not only saves time but also enhances overall efficiency, allowing recruiters to allocate their efforts more effectively.

2. Improved candidate matching

By incorporating multifaceted criteria such as skills, experience, qualifications, and cultural fit, these AI solutions transcend traditional methods. This approach ensures a more nuanced and accurate selection process. This helps in bringing qualified candidates who align with the company culture.

3. Bias-free recruiting

Traditional recruitment processes are often susceptible to unconscious biases, which can lead to unfair and discriminatory practices. AI recruiting software minimizes the impact of bias by relying on objective data and algorithms. It assesses candidates solely based on their qualifications, skills, and experience, ensuring a fair and unbiased recruitment process. An AI-driven objective assessment process fosters a more diverse and inclusive workforce by eliminating biases.

4. Create a personalized candidate experience

AI-powered tools can personalize the hiring process for each candidate, enhancing their overall experience and improving the company's brand reputation. They can analyze candidate data and preferences, enabling a tailored approach to communication and interactions throughout the hiring process.

Instead of generic emails and mass communications, candidates receive personalized messages, relevant information about the company and the role, and prompt responses to their questions or concerns.

Companies that prioritize personalized hiring experiences reap the rewards of an enhanced brand reputation. When candidates feel valued, respected, and well-informed throughout the hiring process, they are more likely to share positive experiences with their networks, leaving a favorable impression of the company.

Also, read: 6 Must Track Candidate Experience Metrics to Hire Better

How does AI hiring tool works?

AI hiring tool operates using a systematic approach that incorporates machine learning and natural language processing. Recruiters use AI in recruitment for planning, analyzing, and organizing redundant tasks. Each industry-specific software might work differently but we can get an overview of how it works. Here's a step-by-step breakdown:

Step 1: Resume parsing

It begins by parsing resumes to extract relevant data such as contact information, skills, education, and work history. An AI-driven recruiting platform uses natural language processing algorithms to read and interpret resumes efficiently.

Step 2: Candidate screening

Once the resumes are parsed, the software analyzes them based on predefined criteria and keywords. It compares the candidates' qualifications and skills with the job requirements, filtering out those who do not meet the specified criteria.

Step 3: Candidate ranking

After the initial screening, AI recruiting software ranks the candidates based on their suitability for the position. The ranking is determined by comparing their skills, experience, and qualifications against those of the ideal candidate.

Step 4: Interview scheduling

Using automated scheduling functionalities, AI recruiting software schedules interviews with the shortlisted candidates. It considers the availability of both the candidate and the interviewer, eliminating the need for endless email threads and time-consuming coordination.

Step 5: Performance analysis

AI hiring tool tracks and analyzes the performance of hired candidates over time. It assesses the quality of their work, their retention rates, and their overall fit within the organization. This feedback loop helps improve the software's algorithms and ensures continuous optimization.

Also, read: How AI is Transforming the Talent Acquisition Process in Tech?

11 Best AI Recruiting Software to Use in 2024

If you're considering adopting AI hiring tool, it might be daunting at first. It can feel overwhelming with so many options out there, each claiming to be the best. This makes choosing the right tool trickier. That's why, we've put together a list of the top 10 AI recruiting softwares:

Different AI recruiting tools you can use and streamline your hiring process

1. HackerEarth

HackerEarth is an end-to-end tech hiring platform, with products that span the entire gamut of tech recruiting needs. It helps with:

Sourcing global tech talent via Hackathons
Assessing and shortlisting candidates via its Assessment and FaceCode platforms
Upskilling and bridging skill gaps via its Learning and Development platform

HackerEarth Assessments

HackerEarth Assessments is an AI-driven coding test platform where tech recruiters can create custom, role-based take-home assessments for screening candidates. It includes a library of over 20,000 questions covering 18+ roles and 900+ skills. Tests are created in under 5 minutes and include built-in proctoring to ensure integrity. After submission, tests are automatically evaluated and benchmarked, generating detailed performance reports.

FaceCode

Shortlisted candidates can be interviewed using FaceCode, a collaborative code editor with real-time feedback features. It includes:

Live coding sessions with instant feedback
Access to a diverse question library
HD video chat and diagram board for deeper interaction

Learning and Development

HackerEarth’s Learning and Development platform uses AI-curated learning paths to upskill teams and close skill gaps through continuous learning and evaluations.

2. Manatal

Manatal is an AI-powered tool that streamlines hiring from sourcing to onboarding. It identifies best-fit candidates and automates repetitive tasks. Its AI scans resumes and social profiles to deliver top candidates, saving time on manual searches.

3. Workable

Workable is a recruitment management system with AI features like resume parsing, candidate ranking, and interview scheduling. It helps recruiters identify top candidates efficiently, reducing the burden of manual resume reviews.

4. Humanly

Humanly features an intelligent chatbot that handles candidate queries in real-time. It integrates seamlessly with your systems and improves engagement through conversational AI and machine learning.

5. Fetcher

Fetcher automates sourcing by delivering curated candidate lists. It saves time on outreach and enhances diversity in hiring, while remaining budget-friendly and highly scalable.

6. Eightfold AI

Eightfold matches candidates to roles based on deeper data including skills, aspirations, and experience. It identifies hidden talent and personalizes the job application experience.

7. LinkedIn Recruiter

LinkedIn Recruiter offers advanced filters and smart algorithms to target the best candidates. Recruiters can view detailed profiles, experience, and recommendations in one place.

8. Eva.ai

Eva AI automates resume screening, sourcing, and interview scheduling. It uses conversational AI to streamline HR tasks, improving the recruiter and candidate experience alike.

9. Findem

Findem goes beyond resumes using a rich data network to match candidates based on attributes and skills. It gives detailed insights into candidate potential and suitability.

10. HumanTelligence

HumanTelligence focuses on behavioral and cultural fit, helping organizations build cohesive, high-performing teams. It supports onboarding and promotes diversity and inclusion.

11. HiredScore

HiredScore uses AI to support unbiased hiring and inclusivity. It analyzes candidate data for fit and provides D&I analytics to help companies build equitable hiring practices.

Selecting the Right AI Recruiting Software for Your Needs

Company size and hiring volume

Choose tools aligned with your company size. Small businesses may prefer intuitive, cost-effective options, while enterprises need robust systems with extensive capabilities.

Industry and target candidates

Some platforms cater to specific industries. For example, healthcare, tech, or customer service sectors may benefit from niche solutions tailored to their hiring criteria.

Budget

Match your tool to your budget. For mid-sized businesses, affordable and scalable tools are ideal. Enterprises may choose comprehensive platforms like Workday or Greenhouse.

Also, read: 6 Steps to Create a Detailed Recruiting Budget (+ Free Template)

Ready to revolutionize your hiring process?

AI recruiting software is transforming how organizations hire. Automation, better matching, and fair selection help recruiters find top candidates faster and more efficiently.

These tools not only streamline communication via chatbots and virtual assistants but also continuously improve through machine learning. They enhance both efficiency and candidate experience.

Organizations that adopt AI recruiting will gain a competitive edge in attracting top talent, driving growth and innovation.

Frequently Asked Questions

Q.1. How AI can be used in recruitment?

AI can analyze resumes and job descriptions, schedule interviews, assess candidates’ skills, and streamline onboarding. Platforms like HackerEarth use AI to evaluate coding skills and automate parts of the hiring process.

Q.2. Will AI replace recruiters?

No. AI supports but does not replace recruiters. It automates repetitive tasks, while humans bring empathy, strategic thinking, and relationship-building—essential for successful hiring decisions.

Revolutionizing Mobile Talent Hiring: The HackerEarth Advantage

The demand for mobile applications is exploding, but finding and verifying developers with proven, real-world skills is more difficult than ever. Traditional assessment methods often fall short, failing to replicate the complexities of modern mobile development.

Introducing a New Era in Mobile Assessment

At HackerEarth, we're closing this critical gap with two groundbreaking features, seamlessly integrated into our Full Stack IDE:

Now, assess mobile developers in their true native environment. Our enhanced Full Stack questions now offer full support for both Java and Kotlin, the core languages powering the Android ecosystem. This allows you to evaluate candidates on authentic, real-world app development skills, moving beyond theoretical knowledge to practical application.

Say goodbye to setup drama and tool-switching. Candidates can now build, test, and debug Android and React Native applications directly within the browser-based IDE. This seamless, in-browser experience provides a true-to-life evaluation, saving valuable time for both candidates and your hiring team.

Assess the Skills That Truly Matter

With native Android support, your assessments can now delve into a candidate's ability to write clean, efficient, and functional code in the languages professional developers use daily. Kotlin's rapid adoption makes proficiency in it a key indicator of a forward-thinking candidate ready for modern mobile development.

Breakup of Mobile development skills ~95% of mobile app dev happens through Java and Kotlin — This chart illustrates the importance of assessing proficiency in both modern (Kotlin) and established (Java) codebases.

Streamlining Your Assessment Workflow

The integrated mobile emulator fundamentally transforms the assessment process. By eliminating the friction of fragmented toolchains and complex local setups, we enable a faster, more effective evaluation and a superior candidate experience.

Old Fragmented Way vs. The New, Integrated Way — Visualize the stark difference: Our streamlined workflow removes technical hurdles, allowing candidates to focus purely on demonstrating their coding and problem-solving abilities.

Quantifiable Impact on Hiring Success

A seamless and authentic assessment environment isn't just a convenience, it's a powerful catalyst for efficiency and better hiring outcomes. By removing technical barriers, candidates can focus entirely on demonstrating their skills, leading to faster submissions and higher-quality signals for your recruiters and hiring managers.

A Better Experience for Everyone

Our new features are meticulously designed to benefit the entire hiring ecosystem:

For Recruiters & Hiring Managers:

Accurately assess real-world development skills.
Gain deeper insights into candidate proficiency.
Hire with greater confidence and speed.
Reduce candidate drop-off from technical friction.

For Candidates:

Enjoy a seamless, efficient assessment experience.
No need to switch between different tools or manage complex setups.
Focus purely on showcasing skills, not environment configurations.
Work in a powerful, professional-grade IDE.

Unlock a New Era of Mobile Talent Assessment

Stop guessing and start hiring the best mobile developers with confidence. Explore how HackerEarth can transform your tech recruiting.

A New Era of Code

Vibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change makes software more accessible to everyone. In the past, being able to produce functional code was a strong advantage for developers. Today, when code is produced quickly through AI, the true value lies in designing, refining, and optimizing systems. Our role now goes beyond writing code; we must also ensure that our systems remain efficient and reliable.

From Machine Language to Natural Language

I recall the early days when every line of code was written manually. We progressed from machine language to high-level programming, and now we are beginning to interact with our tools using natural language. This development does not only increase speed but also changes how we approach problem solving. Product managers can now create working demos in hours instead of weeks, and founders have a clearer way of pitching their ideas with functional prototypes. It is important for us to rethink our role as developers and focus on architecture and system design rather than simply on typing c

The Promise and the Pitfalls

I have experienced both sides of vibe coding. In cases where the goal was to build a quick prototype or a simple internal tool, AI-generated code provided impressive results. Teams have been able to test new ideas and validate concepts much faster. However, when it comes to more complex systems that require careful planning and attention to detail, the output from AI can be problematic. I have seen situations where AI produces large volumes of code that become difficult to manage without significant human intervention.

AI-powered coding tools like GitHub Copilot and AWS’s Q Developer have demonstrated significant productivity gains. For instance, at the National Australia Bank, it’s reported that half of the production code is generated by Q Developer, allowing developers to focus on higher-level problem-solving . Similarly, platforms like Lovable or Hostinger Horizons enable non-coders to build viable tech businesses using natural language prompts, contributing to a shift where AI-generated code reduces the need for large engineering teams. However, there are challenges. AI-generated code can sometimes be verbose or lack the architectural discipline required for complex systems. While AI can rapidly produce prototypes or simple utilities, building large-scale systems still necessitates experienced engineers to refine and optimize the code.

The Economic Impact

The democratization of code generation is altering the economic landscape of software development. As AI tools become more prevalent, the value of average coding skills may diminish, potentially affecting salaries for entry-level positions. Conversely, developers who excel in system design, architecture, and optimization are likely to see increased demand and compensation.
Seizing the Opportunity

Vibe coding is most beneficial in areas such as rapid prototyping and building simple applications or internal tools. It frees up valuable time that we can then invest in higher-level tasks such as system architecture, security, and user experience. When used in the right context, AI becomes a helpful partner that accelerates the development process without replacing the need for skilled engineers.

This is revolutionizing our craft, much like the shift from machine language to assembly to high-level languages did in the past. AI can churn out code at lightning speed, but remember, “Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” Use AI for rapid prototyping, but it’s your expertise that transforms raw output into robust, scalable software. By honing our skills in design and architecture, we ensure our work remains impactful and enduring. Let’s continue to learn, adapt, and build software that stands the test of time.

Ready to streamline your recruitment process? Get a free demo to explore cutting-edge solutions and resources for your hiring needs.

What is Systems Design?

Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.

Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.

Systems Design, in its essence, is a blueprint of how software and applications should work to meet specific goals. The multi-dimensional nature of this discipline makes it open-ended – as there is no single one-size-fits-all solution to a system design problem.

What is a System Design Interview?

Conducting a System Design interview requires recruiters to take an unconventional approach and look beyond right or wrong answers. Recruiters should aim for evaluating a candidate’s ‘systemic thinking’ skills across three key aspects:

How they navigate technical complexity and navigate uncertainty
How they meet expectations of scale, security and speed
How they focus on the bigger picture without losing sight of details

This assessment of the end-to-end thought process and a holistic approach to problem-solving is what the interview should focus on.

What are some common topics for a System Design Interview

System design interview questions are free-form and exploratory in nature where there is no right or best answer to a specific problem statement. Here are some common questions:

How would you approach the design of a social media app or video app?

What are some ways to design a search engine or a ticketing system?

How would you design an API for a payment gateway?

What are some trade-offs and constraints you will consider while designing systems?

What is your rationale for taking a particular approach to problem solving?

Usually, interviewers base the questions depending on the organization, its goals, key competitors and a candidate’s experience level.

For senior roles, the questions tend to focus on assessing the computational thinking, decision making and reasoning ability of a candidate. For entry level job interviews, the questions are designed to test the hard skills required for building a system architecture.

The Difference between a System Design Interview and a Coding Interview

If a coding interview is like a map that takes you from point A to Z – a systems design interview is like a compass which gives you a sense of the right direction.

Here are three key difference between the two:

Coding challenges follow a linear interviewing experience i.e. candidates are given a problem and interaction with recruiters is limited. System design interviews are more lateral and conversational, requiring active participation from interviewers.

Coding interviews or challenges focus on evaluating the technical acumen of a candidate whereas systems design interviews are oriented to assess problem solving and interpersonal skills.

Coding interviews are based on a right/wrong approach with ideal answers to problem statements while a systems design interview focuses on assessing the thought process and the ability to reason from first principles.

How to Conduct an Effective System Design Interview

One common mistake recruiters make is that they approach a system design interview with the expectations and preparation of a typical coding interview.
Here is a four step framework technical recruiters can follow to ensure a seamless and productive interview experience:

Step 1: Understand the subject at hand

Develop an understanding of basics of system design and architecture
Familiarize yourself with commonly asked systems design interview questions
Read about system design case studies for popular applications
Structure the questions and problems by increasing magnitude of difficulty

Step 2: Prepare for the interview

Plan the extent of the topics and scope of discussion in advance
Clearly define the evaluation criteria and communicate expectations
Quantify constraints, inputs, boundaries and assumptions
Establish the broader context and a detailed scope of the exercise

Step 3: Stay actively involved

Ask follow-up questions to challenge a solution
Probe candidates to gauge real-time logical reasoning skills
Make it a conversation and take notes of important pointers and outcomes
Guide candidates with hints and suggestions to steer them in the right direction

Step 4: Be a collaborator

Encourage candidates to explore and consider alternative solutions
Work with the candidate to drill the problem into smaller tasks
Provide context and supporting details to help candidates stay on track
Ask follow-up questions to learn about the candidate’s experience

Technical recruiters and hiring managers should aim for providing an environment of positive reinforcement, actionable feedback and encouragement to candidates.

Evaluation Rubric for Candidates

Facilitate Successful System Design Interview Experiences with FaceCode

FaceCode, HackerEarth’s intuitive and secure platform, empowers recruiters to conduct system design interviews in a live coding environment with HD video chat.

FaceCode comes with an interactive diagram board which makes it easier for interviewers to assess the design thinking skills and conduct communication assessments using a built-in library of diagram based questions.

With FaceCode, you can combine your feedback points with AI-powered insights to generate accurate, data-driven assessment reports in a breeze. Plus, you can access interview recordings and transcripts anytime to recall and trace back the interview experience.

Learn how FaceCode can help you conduct system design interviews and boost your hiring efficiency.