Two-thirds of hiring team members use AI – but how?

AI, of course, rocked our world. But for those of you who hire and employ, let’s understand what’s going on in AI in hiring.

The first – and most basic – question we asked of recent hiring team members in our AI in Hiring & Work survey is simply: when hiring, did you use some form of AI when doing so?

Nearly two in three respondents (62.5%) said yes.

That 62.5% of respondents brings us to a total of 950 hiring team members who have:

1) hired within the past year
2) used some form of AI in the hiring process

This gives us a rich opportunity to get deeper in this area.

The use cases of AI in hiring

First off, we asked respondents to choose three items from a comprehensive list of potential use cases of AI in hiring. Two major purposes for AI in hiring stood out: identifying potential talent, and optimizing the hiring process.

Talent identification

Respondents told us that AI is most used as a tool to help identify the right kind of candidates in the overall applicant pool. In other words, out of the entire pool, they’re using AI to extract the good ones worthy of a deeper evaluation.

Resume screening (58.9%) and candidate matching (43.1%) were by and far the top two most popular use cases for AI in recruitment.

But interestingly, only 8% of hiring team members used AI to source candidates – even though there are many tools out there that can do so, such as Workable’s AI Recruiter technology.

Logistical processes

As you work down the list of how AI is being used in hiring processes in the US and UK, the purpose becomes more logistics focused.

In other words, speeding up the overall process, freeing up bandwidth, and reducing bottlenecks in the hiring team – and AI supports the optimization and automation of steps with those goals in mind.

For instance, interview scheduling (37.6%), assessments (19.9%), and background checks (16.4%) are the third, fourth, and seventh most popular items in the list of 11 in total.

Compensation analysis (6.7%) and diversity analytics (6.6%) are the least popular items.

The industry lens

Not all hiring teams are the same, obviously – especially when looking through industry lenses.

Where resume screening leads the way in terms of what AI is being used for in the hiring process, it’s even more so for those in Accounting / Finance, where seven out of 10 hiring team members (70%) use AI in resume screening. That’s a full 11.1 points above the overall baseline of 58.9%.

That sector, however, is also less likely to use AI for candidate matching (36.3%) than all respondents (43.1%).

Meanwhile, Manufacturing (51.9%) and Retail (52.2%) are less likely to use resume screening. They are, however, much more likely than the overall to use candidate matching technologies (54.5% and 50.7% respectively, vs. 43.1% overall).

AI in video interviews is more popular with those in IT / Technology / SaaS (26.3% vs. 19.4% overall) and less so in Healthcare (12.7%) and Retail (13.4%).

When it comes to AI in assessments, Education is far more likely to use AI (29.9% vs. 19.9% overall) and Construction less so (13.3%).