We’ve highlighted in previous blog posts how artificial intelligence (AI) can source candidates or screen resumes, but is there a role for AI in the interview process? This blog explores the opportunities available as AI enters the very human space of interviewing, and provides details to consider before implementing your own AI solution.
According to CNBC, 51% of Fortune 500 companies use some kind of AI in their hiring processes. However, AI is used for relatively low-level tasks, including automating activities related to sourcing and screening potential candidates and scheduling interviews. Only 36% of talent acquisition professionals said they use AI in the candidate interview process.
Let’s explore common interviewing challenges and examples of companies successfully utilizing AI to solve them:
Challenge: Candidates are dissatisfied with vague job descriptions and impersonal emails and want to receive more detailed information about the job opportunity and company.
AI solution: Utilization of AI-powered assistants for initial candidate assessment.
AI example: Marriott International announced the launch of MC, Marriott Careers chatbot for Facebook Messenger. MC imitates human speech patterns while guiding users to apply for open jobs based on discipline and location and also provides information about the company culture and values. It answers questions, such as: “Do you have event manager job openings in Chicago? How do I get in contact with a recruiter? What are Marriott’s core values?”
A short quiz provides an interactive way to decide which of the organization’s 30 brands may suit the applicant’s interests.
“You can get a direct, real-time dialogue instead of submitting a question and waiting for a response,” says David Rodriguez, executive vice president, and global chief human resources officer for Marriott.
Challenge: Scheduling delays and other logistical complications mean employers miss out on qualified candidates and burden recruiters with manual scheduling tasks.
AI solution: Text conversations between candidates and an AI platform.
AI example: Mya Systems, an AI platform founded by Eyal Grayevsky, engages with candidates via text, asking basic questions such as start date and salary requirements. Potential employees can also ask Mya questions, and she’ll either respond or ask a live recruiter for an answer.
Using a preprogrammed assessment model, Mya either moves candidates to the next step in the hiring process or rules them out. Interestingly, those who interacted with Mya reported in 73% of the cases that they’d thought they’d been speaking with a human recruiter (CNBC).
Challenge: Hiring managers are subjective when it comes to evaluating and selecting the right candidates, which according to Harvard Business Review contributes to the prevalent gender segregation of jobs. For example, male bankers tend to hire more male bankers and female teachers hire more female teachers.
AI solution: Video interviews independently scored by an AI solution with the best matches forwarded to a human recruiter. The AI output includes observational notes for each candidate, including the interviewee’s facial expressions, mood analysis, and personality traits.
AI example: Unilever improved the diversity of its talent pool by 16% since partnering with HireVue, according to HireVue’s CEO Kevin Parker. HireVue offers a customizable AI solution to help assess candidates’ video interviews.
The AI gives each video a score based on more than 250,000 data points, including audio, tonality, and speech patterns, the importance of which can be customized for the client’s need. Because of machine learning, the AI can refine its accuracy over time based on new data.
That’s not to say AI is infallible. As we shared in a previous post, “the computer science adage ‘garbage in—garbage out’ is apt because, despite the prevailing perception otherwise, humans have control over AI programming. Remember that a system is only as good as its data!”
Case in point: According to a Reuter’s story, Amazon canceled an AI-based hiring program that it started in 2014 after it showed bias against women. The program utilized machine learning algorithms to automatically rate resumes submitted by people seeking technical jobs. Over time, it rated women’s resumes lower. In effect, Amazon’s system taught itself that male candidates were preferable.
What we’ve learned
Implementing AI for recruitment is a growing trend, and McKinsey Global Institute predicts 70% of all companies will implement some form of AI by 2030.
Where AI fits in your hiring process will depend on where your organization is in its human resources (HR) maturity.
- Mature HR organizations with advanced practices may be ready to use AI for cognitive engagement like video scores.
- Companies with a typical HR practice may benefit from cognitive insights, such as pattern recognition.
- HR departments with developing practices can improve efficiencies with the automation of routine tasks to facilitate the interview process.
MorganFranklin uses a holistic approach to implementing successful AI strategies for their clients. We look at the big picture, apply key learnings, and analyze impacts on the entire organization before making strategic recommendations.
In our next post, we’ll explore effectively using AI during the offer process.