How AI is Revolutionizing Talent Acquisition: Recruitment (pt 2)

** This article is part 2 of a series we are doing on the use of AI in our industry.**

Artificial intelligence (AI) has made its mark in almost every industry, including talent acquisition. The use of AI in talent acquisition is revolutionizing the recruitment process. The recent testing of ChatGPT 4 & Bard on various talent acquisition responsibilities revealed that AI could offer valuable insights and recommendations across a broad spectrum of duties. Among these responsibilities is the pre-screening of resumes.

SCREENING RESUMES

Pre-screening questions are crucial in identifying suitable candidates for a job. These questions filter out candidates who are not a good fit for a particular role because they lack the necessary skills or experience or don't meet other essential criteria such as location, work authorization, or availability. These questions are typically asked early in the recruiting process, often as part of an initial screening phone call or online application process.

AI can help talent acquisition professionals automate the initial screening process, which can save talent acquisition professionals significant time and effort. AI-powered systems can ask candidates pre-screening questions and use natural language processing to analyze the responses to determine if they meet the qualifications for the position. Additionally, AI can ask follow-up questions to further narrow the pool of candidates and help identify the best fit for the job.

AI can ask pre-screening questions in many ways, depending on the specific needs of the recruiting team and the available technology. One common approach is to use chatbots or other conversational AI tools to ask questions in a conversational format, either through text or voice-based interactions.

For example, let's say a talent acquisition team is looking to fill an account executive position, and they have identified several key qualifications that are important for success in this role, including a track record of success in sales, experience working with large enterprise clients, and the ability to manage a large sales pipeline. They might use an AI-powered chatbot to ask questions to assess these qualifications. The chatbot might start with basic questions to confirm the candidate's interest in the role and availability.

For example, it might ask:

Chatbot: Hello! Thank you for your interest in our account executive position. Before we proceed, I have a few questions to ask you. Are you ready to get started?

Candidate: Yes, I am.

Chatbot: Great! First, can you please confirm that you have at least three years of sales experience?

Candidate: Yes, I do.

Chatbot: Excellent. Next, do you have experience selling software products?

Candidate: No, I do not.

Chatbot: I see. Our ideal candidate for this position has experience selling software products. Can you tell me more about your sales experience and how it may relate to our product?

Candidate: Well, I have experience selling other types of products, and I'm a quick learner. I'm confident that I could quickly learn about your product and sell it effectively.

Chatbot: Thank you for sharing that. Next, can you tell me when you exceeded your sales targets?

Candidate: Sure. In my last role, I exceeded my sales targets by 20% in the first quarter.

Chatbot: Impressive! Finally, are you willing to work on-site for this position?

Candidate: No, I don't live in the area anymore.

Chatbot: I see. Unfortunately, working on-site is a requirement for this position. Thank you for your interest, but we will not be able to proceed with your application. We do offer remote positions from time to time, so I encourage you to follow us on LinkedIn. Would you like me to send you appropriate openings when they come open?

In this example, the chatbot asked several pre-screening questions about the candidate's qualifications for the account executive position. As a result, the chatbot filtered out the candidate based on their lack of experience selling software products and their lack of a bachelor's degree, both identified as requirements for the position. The chatbot also asked the candidate to provide specific examples of their sales experience, which helped to assess their suitability for the role.

Pre-screening questions can play a crucial role in identifying the right candidates for a job. When using this tech, however, it is important to differentiate between an employer's preferences and mandatory requirements to ensure that the screening process is fair and unbiased.

Mandatory requirements are qualifications, skills, or experience that an employer deems necessary for the job. These requirements are non-negotiable, and candidates must meet these criteria to be considered for the job. For instance, a job may require a specific certification or license, a minimum number of years of experience, or fluency in a specific language.

On the other hand, an employer's preferences are qualifications or attributes they would like to see in a candidate but are not mandatory for the job. These preferences can include things like a specific degree, experience in a particular industry, or proficiency in a particular software application. While these preferences may give some candidates an advantage, they are not essential to the job.

It is also important for employers to be transparent with candidates about their mandatory requirements and preferences in the job description and pre-screening questions. They can also give candidates feedback on their performance during the pre-screening process and communicate why they were not selected for the job.

In the coming week, we will cover other ways that AI can assist with your Talent Acquisition needs, including conducting Interviews, and negotiating job offers.