The Perfect Mix: Making AI and HR work together in recruitment

As technology and GenAI continues to develop for HR, Martha Delehanty, Chief People Officer at data backup and recovery firm Commvault puts forward a balanced approach for recruitment between AI and HR professionals.

For years forward-thinking organisations have been harnessing technologies like machine learning and intelligent automation to achieve operational efficiency. However, with the launch of Generative AI (GenAI) and tools like ChatGPT, the game has changed – especially in the business world where it’s rapidly transforming a range of functions, including HR. While the potential of this technology is amazing and vast, we are still in the early stages of understanding its full impact. That’s why we must approach this transformation with both optimism and caution, recognising the opportunities and the risks associated with GenAI.

As HR and recruiting professionals, it is critical we get this right from the beginning. We should acknowledge the significant promise GenAI offers, but be equally aware of the associated challenges, such as bias, transparency, and ethical considerations. Further, the opacity of certain algorithms and the widespread access to this technology raise important questions about its trustworthiness.

So, the question is, how do we know we’re doing more good than harm in using GenAI for recruitment? We need to start with understanding the technology and how, when, why, and where we are using it; that will become more important than the technology itself. And as the ethical, legal, and compliance implications are and will continue to be very real concerns, the “human” component of Human Resources will become paramount.

AI and humans both belong in recruitment

GenAI can significantly streamline and enhance the hiring process, offering advanced algorithms and data analytics that can and should be used to automate previously manual and time-consuming tasks, like CV screening for key skills. Scanning vast databases to identify potential candidates using pre-determined criteria is a great use for this technology – as long as we are thoughtful when identifying the screening criteria. That’s where the human piece comes in – what criteria is a “must have” or “nice to have” and what are the implications for our candidate pool when we apply the screening? Is there an adverse impact on certain populations with that selection criteria? If so, is the screening truly essential (or a nice to have) for the job? These can be heady issues with huge implications, both legally and ethically. 

For example, consider an AI system designed to screen resumes based on pre-determined criteria surrounding prior job titles. If trained on biased data, the system might prioritise candidates from certain industries or backgrounds, inadvertently excluding qualified candidates from underrepresented groups. 

Or imagine using an AI system to screen video interviews for social cues that determine effective teaming or communication and training the system to identify “poor eye contact” as a negative indication of effective communications. The system may end up screening out highly qualified candidates simply because they didn’t stare directly at the screen. This is why the human element is so incredibly important, serving as a gatekeeper to ensure AI systems are carefully designed and trained to avoid perpetuating existing biases.

Using AI to find qualified job applicants

When it comes to hiring new talent, opening the recruitment pipeline to the widest possible selection of candidates is key. By automating aspects of the recruiting process to make the search simpler, broader, and deeper, AI can help broaden our candidate pool, which is a good thing. It’s a missed opportunity not to lean in and utilise GenAI, it’s the ultimate ‘work smarter not harder’ mechanism. 

But when it comes to verifying possible applicants, AI-powered pre-employment assessments aiming to understand candidates better can backfire in very real and harmful ways, as shown in the earlier hypothetical situations, where facial expressions and titles were determining factors. The focus must be on getting it right from the beginning so that you pull in qualified applicants and spend the time getting to know the person behind the CV. 

As such, using GenAI for process-oriented tasks is where HR teams can truly succeed. For example, teams can leverage this technology to allow candidates to take assessment tests remotely and use visual cues to determine environmental impacts. This not only showcases a flexible and employee-centric hiring approach, but it can greatly increase a candidate pool.

Getting started

Leaning into the benefits of GenAI is essential to an HR leader’s success – and saving valuable time and effort when it comes to evaluating candidates is just the beginning. Recruiting teams can elevate the quality and personalisation of the interaction with candidates and introduce chatbots to streamline the experience for everyone involved – from candidates, to managers, to back-office teams. 

Now more than ever all HR professions – especially professional recruiters – must remain informed about how and when their company is using AI and provide continuous input to improve the AI systems and tools being deployed. This continuous innovation, thoughtful application of technology, and relentless curiosity are key to our future success.