In this article, we'll explain what an AI ATS is, as well as the key features, benefits, and potential drawbacks of this type of software. We’ll also share top vendors in this category that our HR tech experts have tested and loved.
What Is an AI Applicant Tracking System?
An AI Applicant tracking system or an AI ATS is a type of software designed to smartly engage, evaluate, and rank candidates using cutting-edge algorithms. From resume parsing and ranking to candidate engagement and predictive analytics, this solution is becoming a central part of modern human resources and recruitment strategies.
Let’s examine the key features of an AI applicant tracking system more closely and learn how to use each effectively.
AI ATS Features
Resume Parsing and Ranking
Modern AI-powered ATS systems should let you parse through large volumes of applications and, in a matter of seconds, identify and rank the best candidates based on a variety of complex factors, including criteria set by the recruiter or hiring manager, desired skills and experience, and potential cultural fit.
By using natural language processing (NLP), this feature can interpret the resume content and assign scores based on how well a candidate’s qualifications match the set a job criteria.
How Do You Use It?
Once you customize the candidate screening criteria based on the specific skills, experience, and qualifications essential for your open position, the AI ATS should be able to instantly identify top talent from your applicant pool, saving countless hours you would have spent manually reviewing resumes.
You should also regularly update these criteria to adapt to your company's evolving needs and what’s generally expected of the role. Otherwise, they will be outdated, and as a result, the AI won’t be able to present the profiles with the most relevant skills and work experience to you.
Candidate Engagement
An AI-driven ATS can automate communication with candidates, schedule interviews, and even predict a candidate’s future success in a role based on historical data and sophisticated algorithms. An ATS with AI recruiting capabilities can assist you with attracting and nurturing a quality talent pool.
At the beginning of the recruiting funnel, your candidates may encounter an AI-driven recruiting chatbot that can interact with them in real time, answering their questions and providing information about the company culture. Further down, this conversational AI can schedule interviews and keep them posted on their application status. Knowing how to use this feature can help improve candidate experience while saving your recruiting team’s valuable time.
How Do You Use It?
Chatbots can be used to screen candidates by asking preliminary interview questions. This allows you to quickly gauge a candidate’s suitability and interest in the position before a human recruiter invests time in an interview.
Frequently check in on how the chatbot works by testing it yourself as a job seeker. You can and should also ask for candidate experience with your recruiting process. This will help the candidates feel heard, and at the same time, you gain needed insights into what could be done better.
Predictive Analytics
Before the integration of artificial intelligence, applicant tracking systems operated primarily as digital filing cabinets. For hiring professionals, this meant manually screening resumes and sorting them based on qualifications and other metrics. By nature, this process also involved some subjective calls on how suitable a candidate would be and their expected tenure (i.e., quality of hire).
Modern, AI-driven recruiting tools can handle this review process with due consideration for each candidate. Predictive analytics in an ATS uses past hiring data to forecast outcomes, such as how well a candidate will perform in a role or how long they are likely to stay with the company. This feature helps you make more informed, data-driven decisions, optimizing your recruitment strategy over time.
How Do You Use It?
Review your ATS's predictions regularly and compare them with actual outcomes. This feedback loop allows you to refine the system’s algorithms, making the predictions more accurate and useful.
ATS Re-engagement
AI-driven ATS systems can automatically re-engage past candidates for new job openings that align with their skills and experiences.
For example, as a recruiter, you can access an existing, pre-vetted talent pool before sourcing new candidates. You won’t have to start your candidate search from scratch every time a new position opens up— the AI re-engagement feature lets you touch base with those already in your ATS database that may be an excellent fit for the new role.
How Do You Use It?
ATSs with this feature can periodically review and update the candidate pool in your ATS if tweaked properly. The idea is to be able to reach out to past applicants with personalized messages when new opportunities arise that match their skills and experience, with only a few clicks. The tool would present you with the main fits, and you’d decide whether to re-start the conversation with any of them, or source new ones.
Benefits of an AI ATS
Leveraging AI in applicant tracking systems has key benefits, including improved efficiency, enhanced candidate experience, data-driven decision-making, and reduced human bias.
Improved Efficiency
AI can drastically speed up the recruitment process. By automating tasks like resume screening and interview scheduling, AI allows your recruiting team to focus on what they do best: engaging and evaluating top talent. Imagine reclaiming hours each week that were once lost to mundane administrative tasks – with AI, this is your new reality.
Enhanced Candidate Experience
Candidates expect prompt and personalized communication. AI, through features like chatbots and automated messaging, enables your ATS to keep candidates engaged and informed at every stage of the application process. This not only improves the candidate’s perception of your organization but may also encourage them to advocate for your brand, win or lose.
Data-Driven Decision-Making
AI in your ATS can systematically analyze vast amounts of data to uncover insights that might go unnoticed. By using machine learning algorithms, your system can rank candidates based on objective, quantifiable criteria, enabling you to make hiring decisions that are rooted in solid data, not just gut feeling.
Reduced Human Bias
Perhaps one of the most transformative potentials of AI in recruitment is its capacity to reduce unconscious bias.
Lareina Yee, Senior Partner at McKinsey, believes AI recruiting has a part to play in the growing awareness and actionable steps toward creating more equitable hiring and onboarding processes. In an interview for McKinsey, she said: "Looking at social media, how do people talk about certain capabilities? You may find there are better words to associate with those who have those skills. Think of a world where you want to be able to find candidates who have amazing experience from learning on the job but don’t have PhDs or college degrees. I’m optimistic that this could open more doors for folks like that."
As you integrate AI into your ATS, you are not just streamlining your recruitment process — you are potentially revolutionizing the way your organization identifies and engages with talent.
Drawbacks of an AI ATS
While AI integration in applicant tracking systems offers remarkable benefits, it also comes with its own set of challenges. Four potential drawbacks of AI applicant tracking systems are the risk of algorithmic bias, privacy and data security concerns, dependence on data quality, and cost.
Risk of Algorithmic Bias
AI systems learn from historical data, and if this data contains biases, the AI models can inadvertently perpetuate these biases. A 2020 report from Harvard Business School (HBS) and Accenture titled Hidden Workers: Untapped Talent found that candidates who had gaps in work histories or lacked college degrees were often disqualified by automated screening tools, despite potentially being highly competent.
A potential solution though, is to regularly review and update your AI algorithms and train them with diverse and unbiased data. Work with a diverse team when setting the criteria that the AI will use, ensuring that it doesn’t inadvertently discriminate against certain groups.
Privacy and Data Security Concerns
Collecting and analyzing candidate data raises significant privacy and data security concerns. Job applicants need assurance that the personal information on their candidate profiles will be handled with the utmost care. This is especially important with respect to ATS background checks.
Ensure your ATS complies with all relevant data protection regulations, such as the GDPR in Europe or the CCPA in California. Clearly communicate your data usage policy to candidates and rigorously secure all collected data.
Dependence on Data Quality
The effectiveness of AI depends heavily on the quality of the data it is trained on. Inaccurate or incomplete data can lead to flawed insights and poor decision-making.
Make sure your software provider establish stringent data quality checks and regularly updates the training data for their AI algorithms, and that those same algorithms are shaped by your use of the tool. This ensures that your ATS is making decisions based on the most accurate and current information available.
Costs and Complexity of Implementation
Implementing AI into an ATS can be complex and require a significant initial investment. For example, the best ATS for small businesses may have AI capabilities, but the cost of operating this size of operation can be a substantial hurdle.
To mitigate this issue, you can begin with a phased approach, starting with one or two AI features that address your most pressing needs. This allows you to realize immediate benefits while keeping initial costs more manageable. As you grow and as the ROI becomes clear, you can consider further investments.
Top AI Applicant Tracking Systems
Whether you are a rapidly expanding startup, an established corporation, or something in between, AI-driven ATS solutions can save you time and money while connecting you with the right candidates more efficiently and effectively. Here are some examples of standout AI-driven ATS options in the market:
9 in 10 businesses are using AI in their hiring process. Are you?
Conclusion
AI applicant tracking systems promise efficiency, enhanced candidate experiences, and data-driven insights that can give your company a significant edge in the competitive job market.
However, as with any powerful tool, it comes with its own challenges— from algorithmic biases to data security concerns. It's crucial for you to be proactive, continuously reviewing and refining your system's algorithms and ensuring rigorous data security measures.
