Artificial Intelligence (AI), in its simplest form, is the development of intelligent machines that think, learn, and respond like humans. Depending on your perspective - some find this scary, others find it revolutionary and exciting, but no matter how you see it, it's highly disruptive and changing the landscape of many industries today.

Originating from the minds of early computer science innovators and futurists, humans have been looking for more efficient and effective ways to interact with computers since their inception in the early 20th century. From the first program to play a game of chess in 1948 to modern-day AI assistants we're all familiar with like Siri and Alexa, advancements in AI technology have come a long way.

AI's primary benefit to society lies in its ability to automate complex tasks, save time, and make data-driven decisions. If you're familiar with the Jetsons TV show, you may recall Rosie, the Jetsons' robotic housekeeper who could cook, clean, and do laundry - AI recruitment software is the modern-day equivalent for hiring teams. It automates processes that used to be time-consuming and tedious, freeing up recruiters' time to focus on building relationships with candidates and making more strategic decisions.

However, not all AI recruiting tools are created equal. Artificial intelligence recruitment software is a relatively new industry, and the market is flooded with various options boasting features that help teams hire better. But do they live up to their promises? and, if so, how do you choose the best AI recruitment software for your organization? That's what we're going to cover in this article today- How to choose the best artificial intelligence recruitment software for your needs.

In the next couple of sections, we'll build a framework for finding AI-powered tools like assessment platforms and interview intelligence. We'll also discuss the critical components of AI software, including machine learning, natural language processing (NLP), and predictive analytics. Finally, we'll dive into some essential considerations when evaluating AI recruitment tools and wrap up with a few product recommendations to help get you started.

AI For Recruiting

First and foremost, it's essential to identify what specific areas of your recruitment process could benefit from AI recruitment software. This begins with a thorough assessment of your current needs, weaknesses in your current hiring process, and gaps in your hiring tech stack.

Here are some questions to help you get started. Do you need help sourcing candidates? Screening resumes? Scheduling interviews? Interviewing effectively? or helping with coaching interviewers? Do you need to improve your diversity and inclusion efforts? Or are you looking for a tool to help with onboarding?

Once you identify your pain points, it's time to get budget approval. What can you spend to get the best candidates possible? What technology do you need to invest in to support your goals?

Now that you have a clear understanding of what areas of your recruitment process could benefit from AI, let's dive into the features and capabilities you should look for when evaluating different tools.

Machine Learning vs. Artificial Intelligence:

What's the Difference?

Machine Learning (ML) and artificial intelligence (AI) are often used interchangeably, but they are not exactly the same. While AI is a broad term referring to machines that mimic human intelligence, ML is a subset or application of AI that allows systems to learn and improve from experience without being explicitly programmed.

So why does this matter when evaluating AI recruitment software? Understanding the difference can help you identify what features and capabilities are most important to your hiring process.

For example, if you're looking for a tool to screen resumes, ML-powered software will continuously learn from past hiring decisions to improve its candidate-matching capabilities. On the other hand, AI-powered resume screening software may be able to understand natural language and context better, resulting in more accurate candidate screening.

Other essential AI capabilities to look for when evaluating recruitment software include natural language processing (NLP) and predictive analytics.

Natural Language Processing:

A key component of AI for recruiting is NLP. Natural Language Processing (NLP) is a subset of artificial intelligence that deals with understanding and interpreting human language. It allows machines to understand, interpret, and respond to human communication in the same way that humans do.

NLP can be used to automate various tasks within recruiting, such as resume screening and candidate communication. It can also help with diversity and inclusion efforts by removing any gender or racial bias from job descriptions and other hiring materials.

Predictive Analytics:

Another critical component of AI recruitment software is predictive analytics. Predictive analytics uses data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data. In recruitment, this can be used to predict candidate success and job fit, allowing hiring teams to make more informed decisions about who to hire.

So now that you know what they are, how do you "put it all together" and create a real solution to the challenges you listed in your needs assessment? Let's get into that in the next section.

AI Recruiting Software

The best AI recruiting tools offer a handful of features to make your hiring process simpler and more efficient. Here are just a few to help you get started:

1. Applicant Tracking Systems (ATS): One of our favorite ATS systems, Lever, offers a diverse set of recruiting and hiring features, including AI-powered resume screening and candidate matching. This simplifies the process of managing and tracking candidates, keeping all your recruitment data in one centralized system.

2. AI Sourcing: Solutions like HireEZ use AI to identify top talent from a wide pool of candidates using criteria like skills, job preferences, and experience. This saves time and effort for recruiters by quickly finding the best matches for open positions.

3. Interview Intelligence:  Platforms like Pillar use AI-powered interview intelligence to assess candidates' responses and provide objective feedback, eliminating human bias in the interviewing process. It also offers tools for coaching interviewers and improving diversity and inclusion efforts.

4. Onboarding:  AI-powered chatbots through BambooHR allow new hires to ask questions and receive instant answers, making the onboarding process smoother and more personalized- allowing new team members to get "up to speed" faster and at their own pace.

These are just a few examples of AI recruitment software that can significantly impact your hiring efforts. When evaluating different tools, make sure to consider both the features and capabilities mentioned above, as well as any specific pain points or needs identified in your initial assessment.

When evaluating different AI recruiting tools, consider which features will have the most significant impact on your hiring process. And remember that these tools are meant to assist and enhance your current processes, not replace them entirely- which we'll talk about in the next section.

AI For Recruitment

AI for recruitment isn't meant to fully replace the human being, only simplifies and adds efficiencies to the hiring process, eliminating steps that don't require the human touch. As a benefit, AI recruitment software can also remove human bias from the process, resulting in more diverse and equitable hiring practices - but that doesn't mean AI in recruitment examples has been perfect. AI learns from the data it's trained on. Early models that were built in-house at large tech companies like Google and Amazon quickly showed biases toward certain types of workers and were ultimately scrapped.

Luckily, these have been replaced by better models that are showing great promise at eliminating biases altogether. Some examples of successful AI recruitment software implementations show huge increases in diversity hiring. For example, Pillar's interview intelligence software has helped several organizations increase diversity hiring by as much as 59% all while lowering vital metrics like employee turnover and cost-per-hire.

AI in recruitment for 2023 taught the world that AI recruitment software could be used to make great hires while decreasing costs and shortening time-to-hire - a vital metric with today's high demand for talent. But it also showed that in order for AI recruitment to work well and provide the benefits promised, it requires a dedicated team effort. It's not simply a plug-and-play solution, but rather a tool that needs to work in an additive way for HR and recruiting teams. In other words, AI is only as good as the data it's trained on and the team using it.

As we move into 2024, the future of AI for recruitment looks bright. With more advanced models and technologies, we can expect even greater improvements in hiring efficiency and diversity efforts. However, it's up to HR professionals and recruiters to choose the right tools, use them responsibly, and continuously evaluate and improve their processes for optimal success with AI in recruitment.

If you'd like to see how Pillar's AI-powered interview intelligence software can improve your hiring efforts, book your demo today. Our team is dedicated to helping you achieve your recruitment goals and create a more equitable workplace. Let's work together to make the most of AI in recruitment and revolutionize the way we hire.