[Academic] What AI tools are used in recruitment these days and what is the process (stages) behind it?

Hi Simon,

It’s great to see your interest in exploring AI in recruitment! Here’s a comprehensive response to your questions:

1. Stages of Recruitment:
While the recruitment process can vary by organization, a general outline may look like this:

• Job Posting: Creating and sharing the job description across various platforms.
• Application Submission: Candidates submit their applications, often through an applicant tracking system (ATS).
• Preselection: Initial screening of resumes to filter out candidates who do not meet the basic qualifications or criteria.
• Phone/Video Interview: Brief interviews to further assess candidates’ suitability and gauge interest.
• In-Person Interview: More in-depth interviews with selected candidates to evaluate cultural fit and technical skills.
• Assessment/Testing: Depending on the role, candidates may complete skill assessments or work samples.
• Final Decision: Collaborating with the hiring team to choose the best candidate and extend an offer.

2. AI Tools in Recruitment:
Several AI tools are currently being used in recruitment processes, including:

• Applicant Tracking Systems (ATS): Tools like Greenhouse, Lever, or Workable often incorporate AI to enhance candidate filtering.
• Chatbots: Tools like Mya and Olivia help engage candidates in real-time and can answer frequently asked questions.
• Video Interviewing Platforms: Solutions like HireVue and Spark Hire use AI to analyze candidate responses and body language during interviews.
• Assessment Tools: Platforms like Pymetrics assess candidates through game-based assessments to measure skills and fit.

3. Stages Where AI is Most Often Used:
AI tools are typically most prevalent in the following stages:

• Preselection: AI can quickly sift through large volumes of resumes, highlighting candidates based on keywords, previous experiences, or specific qualifications.
• Phone/Video Interview: AI can score candidate responses, analyzing verbal cues and facial expressions to assess their competencies.
• Assessment/Testing: AI-driven simulations or cognitive assessments can be employed to evaluate whether candidates possess the necessary skills.

4. Observations on AI Tools vs. Traditional Methods:
From various discussions within the recruitment community, a few observations emerge:

• Flaws: Some users have noted that AI can inadvertently lead to bias if the training data includes biased patterns. Furthermore, ATS can overlook qualified candidates due to strict keyword matching.
• Preference: There seems to be a mixed response. Some recruiters appreciate the efficiency of AI-driven tools for handling large volumes of applications, while others value the personal touch of traditional methods in understanding candidate fit and culture.

In terms of experience, many recruiters today have been in the field for several years, often in corporations ranging from startups to large enterprises, each with distinct processes and cultures.

I hope this overview gives you a clearer picture for your thesis. Best of luck with your research!

Best,
[Your Name]