AI and the Future of Recruiting Coordination
“Therefore, send not to know
For whom the bell tolls,
It tolls for thee” - John Donne
That is dramatic for an opening. However, dramatic changes have occurred in the market since ChatGPT’s initial launch in November 2022. The world has marveled at the advancement of Generative AI (GAI) and Natural language processing (NLP) models, with many predicting the doom of some positions, like content marketing or entry-level engineering. Several big names have called for a pause on giant experiments to ensure proper guard rails are set before moving forward.
There are countless articles about GAI and its impact on recruiting and candidate experience. This one, in particular, will break down GAI’s impact on the Recruiting Coordinator role and possible downstream effects. Having spent my entire time in recruiting working with or as a recruiting coordinator, I have an incredible love and passion for this group, so I felt it was important to capture my thoughts.
What is a Recruiting Coordinator (RC)?
Here is a quick overview of the primary responsibilities (for a longer article, use the link):
Scheduling interviews
Communicating with candidates
Coordinating recruitment events → This could include job fairs, info sessions, background checks
Maintaining the ATS/Tools
Drafting and sending offer letters
This isn’t an exhaustive list, as the responsibilities of the role change between companies and industries, but a means of establishing a baseline for this article. By doing the rote tasks above, an RC learns the foundational elements of recruiting and recruiting operations (RecOps). Keep this idea, as we will revisit it later. Many recruiting departments will attribute their success and efficiency to the skill of their RCs.
Why will Generative AI disrupt this position?
Many tasks RCs handle are exceedingly manual, repetitive, and require high attention to detail. Because of this, it is a role that is prone to error, especially if an RC loses focus or has an off day (e.g., lack of sleep, etc). Basically, if they are having a human-type day.
For years TA Leaders and RecOps Managers have taken two distinct directions to mitigate human errors:
Way #1: Through automation and tooling. Hearing the need of their customers, Applicant Tracking Systems (ATS) built tools within their systems to help with repetitious tasks like gathering interview availability or reporting. A secondary market of Recruiting Tech companies also popped up, aimed at providing features not present in the ATS or offering a different approach by delivering self-servicing that removed middle-people.
Way #2: Increase the size of the RC team. By bringing in more people to help, the workload is distributed. These new individuals get training but need training on the systems and processes. Incorporating new people which requires ramp time and documentation/knowledge management. It also risks increasing, not reducing, human errors because every hire is different and are still human.
Generative AI, however, is incredibly efficient at these types of manual and predictable tasks with the added benefit of needing little to no ramp time. As a matter of fact, most AI is built to handle these exact situations.
This introduces a John Henry-type situation. Assuming there needs to be a ramp time to train the GAI with the right inputs, it will still work faster, more efficiently, and more accurately than a human counterpart. Furthermore, it would not get tired, need to prioritize a task list or require overtime pay to complete everything assigned to it in a day. In a tight talent market where time is of the essence, a GAI can respond to more candidates than a human RC ever could in under a minute while maintaining a consistent performance.
Outcome: Generative AI likely disrupt this position.
But what about the human touch?
One argument often made about why GAI will not replace humans is that only humans can provide a certain touch or level of customer care. This argument, on the surface, makes a lot of sense. If a candidate calls, they want to speak to a real person who conveys empathy. There is only one problem: candidates rarely call anymore. If they do, it is because:
They’re running late to an interview onsite
The interviewer hasn’t joined
Technology (i.e., Zoom, Google Meet, Teams) isn’t working
But most are still likely to use a text-based communication (e.g. email, text messaging, etc) to inform of these issues. With that being the case, GAI can still handle most candidate requests.
What about if the candidate is running late? Wouldn’t a coordinator call?
Maybe. More than likely, the RC will text the candidate first before calling. But here is another aspect where GAI would be superior to a human RC: a human RC needs to be alerted that the candidate isn’t in the room. A GAI could confirm if the candidate and interviewers are in the interview room (with interviews happening digitally) and then send messages across different platforms (e.g. email, text, Slack, etc) to alert the missing parties in less time than a human-RC could. They could even issue a robo-dialed call with a pre-recorded message. If companies are concerned that a robotic voice is a poor candidate experience, tools like elevenlabs.io can clone any voice in your company (say your CEO) and repeat a script. In effect, GAI can do what a human can’t at the moment: be in two places at once.
But GAI can’t handle an onsite!
True, it can’t. But that isn’t likely a strong enough argument for an FP&A team to approve the headcount or spend, especially if you have an office manager or receptionist already in the office.
Outcome: Generative AI puts another one on the board.
If the RC position is removed from the recruiting ecosystem, what does this mean for the future of Recruiting and RecOps?
Revisiting a topic from earlier, remember how I mentioned that RCs form the foundation of a Recruiting function? By removing the RC position from the recruiting ecosystem, recruiting will fundamentally change, possibly not for the better. Here is why:
RCs who stay in recruiting tend to take two paths: front-of-the-house and back-of-the-house roles. The front-of-the-house roles are candidate-facing, so recruiting and sourcing. They’re known for engaging with the people (candidates and hiring managers) involved in the process. Back-of-the-house roles, though, are different. They are process and technology-facing, so RecOps, People Analytics, and Employer Branding. If the RC role goes extinct, there is no next generation to fill the back-of-the-house roles.
Isn’t this just evolution and wouldn’t the RC role evolve?
Yes, in theory, the role would change but it would be fundamentally different in focus. More than likely, the new RC, if everything is handed over to AI, is an IT Specialist. These specialists would essentially exist to fix any issues in the system when a tool goes down or isn’t operating properly.
So wouldn’t that be more efficient?
Yes, but the unintended consequence is that IT Specialists aren’t likely to want to grow up to be recruiters because their income potential is much higher staying technical and on the revenue side of the business. This means the possible recruiter population dwindles.
But what about those that want to make a jump to the front-of-the-house?
If the IT Specialists make the jump, they are now dealing with more theoretical than applied recruiting based on their work experience and fewer recruiters to train them. This means that innovation in the Recruiting space may start to stagnant. Recruiting departments, therefore, change, which means companies change. But this change could be positive as it would provide a space for seasoned recruiters to coach the next generation in ways they cannot now.
Outcome: You remove one block and the entire structure risks crumbling. This one goes to the humans.
So should all RCs give up now?
Despite it all, I don’t think it is time to throw in the towel and give up. This is because GAI will be better at some aspects of the role than it will be at others. It is best to consider it a partnership for the moment, especially one that can involve. GAI isn’t going away, so the more familiarity you have with it (e.g., prompt engineering, prompt storage), the better position you will be in to see where it can help and possibly how to influence it.
In summary
The impact of AI on the RC position will be multifaceted, with both positive and negative implications. It is important to be aware of these potential impacts and to be prepared to adapt to change. Some of the potential impacts of AI on the RC position include:
Automation of tasks: AI has the potential to automate many tasks that RCs currently perform. This could lead to job losses in some areas, as AI-powered machines can perform these tasks more efficiently and at a lower cost. However, AI could also create new jobs and opportunities for RCs, as it could create new products and services requiring human interaction. Additionally, AI could be used to improve the quality of life for humans, which could create new demand for RC services.
Increased competition: AI could also lead to increased competition for RCs. AI-powered machines are becoming increasingly sophisticated, and they are able to perform a wider range of tasks than ever before. This could make it difficult for human RCs to compete, as they may need to offer the same efficiency or cost-effectiveness as AI-powered machines. However, RCs can still compete by offering specialized skills and services that AI cannot replicate.
It is important to remember that AI is a tool, and it is up to humans to decide how it is used. AI can be used for good or for evil, and it is up to us to ensure that it is used for the benefit of humanity. RCs can play an important role in the development and implementation of AI. They can help to ensure that AI is used in a way that is safe, ethical, and beneficial to all of humanity.
(It's worth noting, by the way, that as we explore the impact of AI on the Recruiting Coordinator position, I generated the last paragraph using Google’s new AI helper in Google Doc and Grammarly to help as well. So while I’m warning about the potential threat of AI to human jobs, if I hadn’t included this, it likely would have gone unnoticed. But hey, at least the AI-generated text is efficient, amiright?)
Disclaimer: The views expressed and opinions expressed in this article are those of the author and they do not necessarily reflect the official policy or position of any other agency, organization, employer, or company. Assumptions made in the analysis are not reflective of the position of any entity other than the author. Since we are critically-thinking human beings, these views are always subject to change, revision, and rethinking at any time. Please do not hold them in perpetuity.
