In the fast-paced world of recruitment, staying ahead requires embracing innovative technologies. One such groundbreaking advancement is Generative Artificial Intelligence (Generative AI) - technology poised to reshape how recruiters operate in 2024. But although it’s said over and over that AI will change the way we work, the game changing use cases are still, at times, obscure.
To bring you up to speed though, today we will delve into the five best use cases of Generative AI in recruitment that we’ve come across to date. First, we’ll explore the definition and potential impact of AI and the paradigm shift it brings to recruitment, followed by the five use cases and the profound benefits it brings to both recruiters and candidates alike.
Let’s dive in.
It’s been said many times before, and after all these years it still holds truth: ‘modern recruitment is broken’. Whether it’s the overreliance on resumes and keywords, a long time to hire or biases in hiring - there’s much work to do still. Over the years, many efforts have been made to solve these problems and technological innovations have definitely improved the overall recruitment experience. But none have yet impacted recruitment in the way that AI is about to.
Because, if you think about where most of the problems within recruitment come from - it’s the fact that recruiters spend a good 20 to 30% of their time on administrative tasks. It’s the reason your time to hire is long. It’s the reason why candidates drop off mid-process, and it’s the reason why many recruiters are only half as effective as they can be.
But, to their defense - it is also clear to see why recruiters have to spend so much time on admin. And that has to do with the way the recruiting process is structured.
And the main culprit is the fact that interviews are what we call: ‘unstructured data sources’. A pool of random words and bits and pieces of information, that need to be turned into a ‘structured data source’ by the recruiters (by taking notes, by sending emails and by logging everything into an ATS) in order for systems to be able to work with it. And the translation of this unstructured data into structure, was up until now always a manual effort.
And that is the fundamental change that AI is bringing to the table. With AI, the translation from unstructured data to structured data, can be done automatically, by a generative AI engine - without any outside help from a human recruiter. And it is this concept that has the potential to eliminate all admin work from a recruiter and as a result, save countless hours of their time. Hours that can be used to really focus on the candidate, and finally put an end to long drawn out processes, and terrible candidate experiences.
So, translating unstructured data to structured data. That all sounds great, but what do we mean by that?
The main source of data that drives the recruitment process are interviews. Conversations are considered unstructured data. It’s your phone screen, your first interview, second interview, etc. And much of the admin work in between two interviews, consists of taking in the unstructured data, and giving it structure (by taking notes and adding them to your ATS, for example, or updating stakeholders on whatever communication is happening). Before generative AI, it was impossible to automatically structure this data. Yes, keyword-based ‘AI’ was a thing, and in some ways it worked. But it was flaky at best.
With Generative AI, we now have the technological capability to transform your unstructured data into an accurate transcript, and let an AI make sense out of all this and do the repetitive grunt work for you!
And not only that - if you train the AI well, and build in the right checks and balances - it does the work faster and better than a human (yep, sorry). But look on the bright side! It means that you as a recruiter can focus on doing the things that you are passionate about - connecting with candidates, building relationships, improving the hiring process and getting better people in.
And this is not something that is far out and will take years to become ‘real’. It is happening at forward thinking companies all over the world, right now! And it’s these companies that are implementing AI within their process, that are pulling ahead of those that don’t. We’ve said it before: but the AI adoption gap is real..
Anyway, with that said, let’s have a look at some of the tangible use cases for generative AI in recruitment right now.
We’ve teased this one in the previous paragraph already, but let’s have a more in-depth look. In the realm of recruitment, administrative tasks often act as a bottleneck, consuming valuable time that could be better utilized for strategic activities. From meticulous note-taking during interviews to updating the Applicant Tracking System (ATS) and sending follow-up emails to candidates and stakeholders, these tasks can be overwhelming for recruiters.
Generative AI in recruitment serves as a game-changer by seamlessly automating these administrative burdens. With a simple click, recruiters can kickstart an AI to generate interview notes, populate the ATS with pertinent information, and craft personalized follow-up emails. This not only expedites the administrative process but also liberates recruiters to focus on the core aspects of their role, such as sourcing for top-notch candidates and nurturing relationships with key stakeholders. The automation of administrative work through generative AI heralds a shift in the recruiter's role, allowing them to redirect their energy towards strategic and relationship-building endeavors, thereby improving overall efficiency and productivity in the recruitment workflow.
The creation of personalized and compelling job descriptions is an important aspect of every hiring cycle, and often demands significant time and effort from a recruiter - especially if you want the job description to be on-brand, and taking into account the Ideal Candidate Profile for the job. With generative AI, it’s possible to generate tailored, on-brand job descriptions with the click of a button.
All you have to do is correctly pre-train your Gen-AI model, or contextually enrich it with a tone-of-voice and a few example job descriptions - and you can generate a new variant in seconds by feeding it the job requirements.
And not only that, if you create the right set-up, you can have your AI recruiting assistant automatically disseminate job postings across various channels to reach a wider audience and optimize the chances of discovering the ideal candidates.
Navigating the stream of resumes in the recruitment process can be a formidable task, often characterized by challenges in screening and shortlisting candidates efficiently.
Generative AI can be your transformative force in addressing these traditional hurdles. The technology's capacity to rapidly analyze and comprehend large volumes of data enables a more streamlined and objective screening process. By discerning relevant qualifications, skills, and experience, generative AI significantly reduces the time and effort traditionally invested in manual resume reviews.
Moreover, it introduces a level of consistency and impartiality, mitigating the impact of unconscious biases that might influence human decision-making. This automated approach not only accelerates the initial stages of recruitment but also enhances the accuracy of shortlisting, ensuring that only the most qualified candidates progress in the hiring process. A typical win-win:).
Effectively managing a multitude of interviews and quantifying assessments poses a considerable challenge in recruitment. Also here, generative AI steps in as a valuable asset in enhancing this part of the hiring process.
The technology can play a pivotal role in scheduling and managing interviews seamlessly. By analyzing the availability of both candidates and interviewers, generative AI optimizes the scheduling process, reducing the logistical complexities that often accompany interview coordination.
Furthermore, AI tools can facilitate automated note taking, store the interviews and let recruiters or hiring managers ask questions about interviews - streamlining the evaluation of candidate qualifications and compatibility with the job role. This not only expedites the decision-making process but also ensures a more standardized and objective evaluation.
The incorporation of generative AI in the interview process transforms it into a more efficient, data-driven, and candidate-friendly experience. Recruiters can focus on the strategic aspects of candidate evaluation, confident in the knowledge that generative AI is handling the logistical details with precision and objectivity.
And to top it off - automating stakeholder communication. Communication is the lifeblood of the recruitment process, involving constant interaction with candidates, hiring managers, and various stakeholders. This intricate web of communication often adheres to established processes, presenting a ripe opportunity for automation through generative AI.
Stakeholder communication, which includes follow-up emails and updates, can be a time-intensive task. Generative AI offers a solution by enabling the automation of these communications. With the ability to understand and derive context from the contents of meetings and interactions, generative AI can craft personalized follow-up emails that resonate with the nuances of each conversation. This not only ensures consistency in communication but also saves recruiters significant time that would otherwise be spent on manual email composition.
The efficiency gains are substantial, allowing recruiters to focus on more strategic aspects of their role, such as relationship-building and strategic planning. In essence, generative AI in stakeholder communication becomes a valuable assistant, freeing up valuable time and enhancing the overall effectiveness of the recruitment workflow.
The transformative potential outlined in the various use cases of generative AI in recruitment is not a vision of the future; it is a reality being embraced by companies globally. Organizations are already leveraging generic generative AI solutions to enhance and streamline their recruitment processes.
The next frontier lies in tailoring this technology to the specific needs and intricacies of individual businesses. Implementing an AI engine into your recruitment process offers the opportunity to customize automation, aligning it seamlessly with the unique operational nuances of your company. The era of one-size-fits-all solutions is evolving into a landscape where businesses can integrate AI technologies that not only automate mundane tasks but do so in a way that reflects the ethos and workflows of the organization.
As companies continue to recognize the value of generative AI in recruitment, the focus shifts toward strategic implementation, ensuring that the AI engine becomes an integral and personalized component of the recruitment arsenal, maximizing efficiency, and contributing to the overall success of the talent acquisition process.
There you have it, the five best use cases for AI that we’ve come across today. And for the observant viewer - yes they are all part of automating parts of the process. Because that’s where the impact of AI is most felt at this moment.
It’s clear to see that the future of recruitment is undeniably intertwined with the capabilities of generative AI. The use cases explored demonstrate the tangible benefits that organizations worldwide are already harnessing. But the key lies not just in recognizing the potential of generative AI but in embracing its adaptability. Companies that embark on the journey of integrating AI engines tailored to their unique operations are poised to redefine efficiency in recruitment and improve it for all stakeholders involved. And that is something that is definitely needed.