Surprisingly, artificial intelligence can transform the entire recruitment industry. How? It offers next-gen smart hiring solutions to streamline recruitment and provide a great candidate experience.
With the recent advancements in the AI/ML industry, HR professionals can consider smart resume parsing, predictive analysis, AI-based applicant tracking systems, and more.
Out of these, AI-based smart applicant tracking systems have gained a lot of traction. These
advanced systems allow HR professionals to identify, evaluate, and engage with the right talent.
Whether you are a hiring manager, professional, business leader, or recruitment agency owner, it's time to consider AI development services for building smart applicant tracking systems. But where to start?
Here, we will explain the role of AI in recruitment, key features, benefits, and challenges in AI-powered applicant tracking systems, and how to build an applicant tracking system.
So, let's start.
What is AI in Recruitment?
AI for recruitment uses artificial intelligence technologies to streamline various aspects of the hiring process. These include resume screening, conducting pre-employment assessments, candidate matching, interview scheduling, and more.
By using AI for recruitment, HR professionals can save valuable time and effort. AI enables them to improve the quality of candidate matches, reduce biases, and make decisions based on data. Lastly, AI for recruitment can transform the entire hiring industry by improving the efficiency and effectiveness of sourcing the right candidates for organizations.
What Actually is an AI-Based Applicant Tracking System?
An AI-powered applicant tracking system reduces recruiters' workloads by automating repetitive tasks. These tasks include resume screening and interview scheduling, allowing recruiters to spend more time on strategic decision-making.
The incredible thing about the applicant tracking system is its potential to improve hiring quality by identifying candidates according to their talent and skills, thus reducing biases and taking efficiency to a new level. This kind of applicant tracking system is not just great for your organization but also best for providing a next-gen experience to the candidate
Technologies Needed for Building an AI-Based Applicant Tracking System
Here are some essential technologies HR recruiters and businesses should consider in an applicant tracking system.
Machine Learning
Machine learning is a branch of artificial intelligence that emphasizes developing systems that learn from data without any explicit programming. ML in the applicant tracking system coincides with the historical data to discover patterns, predict outcomes, and rank applicants according to their skills and expertise. Further, ML continuously makes improvements when it comes to accuracy and efficiency, ensuring that the recruitment process becomes super smooth.
NLP
Natural language processing ensures that the applicant tracking system understands and interprets human language. NLP-based algorithms make NLP-powered candidate screening possible. They are further utilized to parse and extract resumes, cover letters, and job descriptions.
In other words, the algorithm enables semantic matching, which means analyzing the candidate based on skills and experience instead of the keywords. Ultimately, this leads to a precise candidate screening and better role alignment.
Bias Detection Algorithms
Bias detection algorithms are beneficial in the AI-powered applicant tracking system to identify and minimize biases in the candidate selection process. Rather than focusing on the discrimination factors, such as gender, ethnicity, or age, these factors consider qualifications, skills, and experience. Ultimately, this results in a fairer and unbiased candidate evaluation, thereby hiring merit-based candidates.
Predictive Analysis
Predictive analytics allow the ATS to forecast hiring outcomes based on their past recruitment strategy and candidate sourcing channels. It also allows HR professionals to predict candidate success, time-to-hire, and employee attrition rates. All the predictive data obtained enables recruiters to make future decisions, such as catering to growing workplace needs and optimizing the overall recruitment strategy.
Key Features of AI-Powered Applicant Tracking System
Here are some essential features you should consider integrating into an applicant tracking system.
- Resume Parsing and Ranking: AI-based ATS automatically extracts the most essential information from resumes and stores all the data appropriately. It further leverages algorithms to check the performance of the candidates according to relevance and rank them effectively. This process speeds up the screening process and saves recruiters valuable time.
- Chatbots for Initial Candidate Interaction: AI chatbots converse well with candidates during recruitment. These chatbots answer users' queries and collect their essential information. This enhances the candidate's overall experience and enables recruiters to focus on more critical tasks.
- Bias Reduction via Tools: AI tools are built to reduce recruitment bias by evaluating and hiring candidates based on their skills and experience rather than their demographics and other factors.
- Integration with CRM System: The AI-based applicant tracking system flawlessly integrates with a CRM system, enabling appropriate data sharing and communication. The newly added CRM also improves collaboration between the recruitment teams and other departments in the organization.
Benefits of AI-Powered Application Tracking System
Organizations and HR professionals get several benefits from using AI-powered applicant tracking systems.
- Reduce time to Hire and Operational Costs: The AI-based applicant tracking system streamlines various tedious tasks, such as resume screening and interview scheduling. This ultimately reduces operational costs and enables the team to invest their resources appropriately.
- Improve Candidate Offering and Onboarding Process: With graceful communication and offering a tailored experience, AI improves the entire candidate offering. This leads to simplified onboarding processes and ensures new employees instantly adapt to the company culture.
- Improved Scalability and Efficiency: Applicant tracking systems quickly adjust to an organization's recruitment needs. This further allows organizations to scale hiring efforts in the right direction without considering quality issues. This level of flexibility promises that hiring teams have enough resources to handle massive hiring during peak seasons.
- Make Data-Driven Hiring Decisions: AI scrutinizes a large amount of candidate data to provide detailed insights and suggestions. This allows recruiters to make valuable decisions based on their goals.
- Advanced Skill Matching and Predictive Workforce Alignment: Using the generative AI services in the applicant tracking systems can help organizations revolutionize skill gap analysis and workforce planning. By combining a massive amount of data, the ATS can determine current role requirements, suggest upskilling opportunities, and produce relevant strategies for workforce alignment. These things ultimately help HRs to thrive in talent acquisition and retention.
Challenges of AI-Powered Applicant Tracking System
Here are several common challenges that organizations, businesses, and HR professionals face while using smart hiring solutions.
- Security Issues: ATS are vulnerable to data breaches and other cybersecurity threats, further exposing the candidate data and organization's information.
- Implementation Costs: AI-based ATS involves different types of costs, such as software, infrastructure, and training. These costs are significantly higher for smaller organizations.
- Ethical Issues: The use of artificial intelligence can raise various ethical concerns, especially in the case of algorithmic bias. If the system is trained partially, it may provide results in the favor of certain parties, which is not good.
- Data Privacy: Due to tough data protection laws and regulations, any organization must keep candidate data confidential. Failing to protect the data can lead to various legal issues.
How to Build an AI-Based Smart Applicant Tracking System?
Here is the simple step-by-step process to build an AI-based Smart Applicant Tracking System:
- Define Your Requirements: Research and determine your organization's initial struggles. Then, list the key features that can resolve these hurdles, such as resume parsing, candidate tracking, and required third-party integrations.
- Choose the Right Technologies: To improve your ATS, choose the most suitable AI technologies, such as machine learning, NLP, etc. Ensure that the technologies simplify your daily tasks and enhance candidate matching.
- Develop the Core Features: Develop the ATS's core features, such as resume parsing, ranking algorithms, chatbot integration, and bias detection tools.
- Integrate with Current Systems: Please ensure the ATS integrates well with HR tools, CRM platforms, and leading job boards for managing tasks and workflow.
- Train and Test the System: Integrate all the necessary historical data into the system to train the AI. Conduct tests at regular intervals to check the accuracy and transparency of the output.
- Implement Robust Security Practices: To protect candidates' sensitive data, implement robust security measures, such as encryption, access controls, and compliance frameworks.
- Deploy and Track the Performance of ATS: Launch your ATS and obtain user feedback. Plus, track how the system is performing and make necessary adjustments to get the desired results.
Final Thoughts
In the end, it's clear that AI-based applicant tracking systems will transform the entire recruitment industry by automating processes, reducing biases, and helping with data-driven decision-making. Innovative features such as resume parsing, chatbots, and predictive analytics help organizations hire the most suitable talent as needed.
With the help of an AI-based applicant tracking system, organizations can consider the right technologies to improve recruitment strategy and offer a great candidate experience. Moreover, by using these technologies and resolving crucial security issues on the go, organizations and HR professionals can optimize the hiring process regularly.
