AI Recruiting

Per a recent Gallup survey, 7 in 10 Americans believe AI tech will eliminate more jobs than it creates. The numbers are all over the map based on different research, but many land within the 47-54% range of all current jobs being automated out.

What does that mean for a recruiter? Is this the beginning of the end?  Will a machine be filling open roles automatically? Will recruiters themselves be entering the job search market?

Or, the flip side: will AI be a welcome enhancement to the recruiting role, making the recruiter’s day-in-the-life more fulfilling?

What do trucking and recruiting have in common?

This is not an intro to a joke.

Like any early technological change, speculation tends to rule the roost. From a practical purpose, however, it’s difficult to imagine AI completely replacing all aspects of a job. As posted recently on The Verge:

Even in high-risk industries like truck driving, there’s only so much automation can do. A computer can drive on a highway, yes, but it can’t repair a truck, unload its inventory, argue with unhelpful warehouse managers, or even refill the gas tank.

How does that relate to recruiting?

“the most important steps in the recruiting process are the human ones: building relationships with prospects, sharing the company culture, handling the irrationalities of candidates and hiring managers, and closing job reqs”

If you look at the trucking analogy, driving is the most time-consuming and monotonous part of that role.

If we look at recruiting, we can break down the functions into tasks that require a high-touch human element, and those that are repetitive and monotonous, and would lend themselves to automation. I.e., the “driving”-equivalent tasks.

From my perspective, the most important steps in the recruiting process are the human ones: building relationships with prospects, sharing the company culture, handling the irrationalities of candidates and hiring managers, and closing job reqs.

But the reality of the current recruiting model shows that less than 40% of recruiting time is spent on these important and high-value tasks. Sadly, it might be even lower than that.

Unfortunately, the bulk of a recruiter’s time is spent on monotonous and time-consuming tasks – the “driving”.   Things such as pouring over résumé́ databases, writing complicated Boolean searches, guessing which companies might provide candidates, dealing with the constrictions of LinkedIn InMail, scheduling, etc.

On the positive front, these are the exact activities that can be executed by AI at scale, and where AI will have a massive impact in shifting the time allocation to higher value tasks. As noted in the Gallup survey above:

While Americans agree that AI adoption will result in a net loss of jobs, they remain largely positive about the impact the new technology will have on their lives and work over the next decade.

This is one area where AI will be positively impacting recruiting and in a big way.

AI’s specific impact on recruiting

When it comes to candidate sourcing, weeks and months of tedious efforts can be executed in minutes using AI. No need to ask the hiring manager for their list of companies to target, or spend time grinding through résumé́ databases. Based on specific targeting — such as years of sales experience, base salary range, technology stacks, etc. — AI will analyze hundreds of variables across millions of companies to define the right targets at a scale not possible in any other way. It will also analyze candidate data and deliver a wide range of candidate pools based on sophisticated scoring techniques. All of this occurs in real-time, so recruiters get immediate results.

Additionally, AI will return predictable conversion rates and timelines, enabling recruiters to communicate to hiring managers the number of candidates available for outreach, as well as the expected follow-on conversion rates: how many responses expected, number of screening calls that will be made, the size of the qualified candidate pool, and the hire timeline.

Being able to present the required candidate pool size and the “projected role fill date” is an effective way to manage expectations.

AI can impact other time-consuming recruiting activities.  AI can automate the outreach to candidates, making it easier to be more personalized, relevant and effective.  AI allows recruiting managers to keep tabs on their target candidate sets more easily. AI-based triggers drive follow-up communications at key moments. This “right-time, automated interaction” drives higher conversion rates and more successful recruiting.

AI and Recruiting – the time is now

AI is a transformational technology that can have a disruptive impact on recruiting management. We’ve been talking about HR departments getting more data-driven and getting that “seat at the table” for literally decades. By leveraging AI, that can happen.

Recruiting managers will vastly improve candidate identification and matching, provide better-recruiting predictability and accurate forecasts for candidate fulfillment, and reduce overall recruitment costs and reliance on third-party staffing agencies.

Recruiters need to pay attention to the impact of AI. Harvard Business Review summarizes it perfectly:

If managers aren’t ramping up experiments in the area of machine learning, they aren’t doing their job. Over the next decade, AI won’t replace managers, but managers who use AI will replace those who don’t.

Find out more about AI and Recruiting

If you’re interested in learning more about how other companies are taking advantage of AI in their recruiting process, and learn how you can use AI, you can easily contact us and/or schedule a demo at


Josh McBride is the co-founder of Upsider. Upsider provides a Recruiting Management System (RMS) that uses Artificial Intelligence to immediately identify the total pool of candidates in any US city based on metrics about the role and business. The Upsider RMS also forecasts the internal resources required to make a hire, and automates the candidate outreach and nurturing process across channels (email, social media, etc). Josh spent his career scaling revenue for data-driven SaaS businesses in highly competitive markets, primarily focused on helping organizations leverage data to gain more revenue, productivity, and efficiency.