The rapid development of AI and the level of automation that comes with it means companies can now target candidates with unprecedented precision, streamline their hiring processes and enhance employee satisfaction. At least, that’s the theory!

If you sense slight trepidation in my tone, it’s not that I don’t think AI is revolutionising our industry. When it’s working well, this transformation in recruitment improves efficiency and positions HR teams to free up time to drive strategic changes.

Traditional methods of attracting top talent need to be updated in an environment that has in recent times witnessed both the Great Resignation and the concept of Quiet Quitting. AI is able to assist HR processes, automating tasks such as sourcing and screening candidates, conducting pre-employment assessments, and even predicting candidate success and cultural fit. But I do think we need to proceed with a level of caution when it comes to AI implementation.

While AI offers transformative potential in HR, its implementation comes with significant risks. These need to be addressed quickly because the AI revolution in HR is already here, and it’s not slowing down. A McKinsey study shows that generative AI is potentially increasing HR productivity by up to 30%, enabling faster content creation and visualisation, while driving the automation of over 50% of onboarding tasks. This is on top of much-improved recruitment engagement rates. So, there is much to gain.

In this article, I argue that harnessing AI in HR is crucial, and understanding the challenges is equally vital. We need to think about the perpetuation of biases that can be embedded in AI algorithms, the problems associated with over-reliance on technology that can overshadow those vital human elements essential for nuanced decision-making, as well as concerns around data privacy and security.

Addressing these issues and ensuring transparency means we can work in a more tailored, personalised way with candidates, make our processes more automated, and make our overall approach more employee-friendly.

The AI train has left the station – the question is, are you on board?

Making your recruitment efforts more tailored

Let us start with how we can use AI to create more personalised engagement with candidates. Generative AI now allows organisations to craft more tailored and effective job descriptions by analysing the attributes and preferences of successful candidates.

This technology enhances communication and better aligns with the expectations of potential hires. It can also strengthen candidate relationship management by maintaining ongoing communication with prospective candidates, updating them on job openings and cultivating a talent pool for future opportunities. Generative AI can also be used to create job postings based on skill profiles, specific keywords or previous ads that are known to have worked well.

The challenge here, in my view, is ensuring the AI-created content doesn’t become generic, signalling to the candidate that little effort has been put into a job description or communication. For example, it’s important to use AI as part of a wider human-led creative process, rather than simply pasting in whatever ChatGPT or another AI-powered app has come up with.

Making your recruitment efforts more automated

AI can be used to identify potential candidates on LinkedIn, so your organisation can send an automated message inviting them to apply. Organisations can also use Natural Language Processing (NLP) to rapidly scan CVs as a way of assessing experience, searching for keywords as well as other indicators to determine if a candidate should move forward. This can be helpful in the early stages while you are working through hundreds of applicants.

AI tools and chatbots can also assist with scheduling interviews, generating job-specific interview questions, and even evaluating candidate responses. Studies reported in the Harvard Business Review have shown that nearly 86% of employers now utilise technology in this way, with a significant increase in the use of automated video interviews (AVIs). But again, there are challenges. The Berkeley Haas Center for Equity, Gender, and Leadership noted that almost half of AI systems exhibit gender bias, and around 25% display gender and racial bias. This is where we must be aware that AI is going to replicate human biases and we need to ensure we’re not making the assumption that the technology is working in a purely objective manner.

Making your recruitment efforts more verifiable

Are people really who they say they are? Verifying CV accuracy used to involve numerous phone calls, which was time-consuming and still prone to errors – it’s not unheard of for individuals to use friends to pose as former employers. So, to thoroughly investigate an employee’s background, including criminal records that could disqualify them from a position, companies traditionally perform background checks or rely on internal resources, which was costly and labour-intensive.

AI-driven solutions now enable rapid verification of multiple resumes in minutes. Established background check providers are integrating AI into their processes, while new AI-focused solutions offer affordable background checks for employers. This can create significant savings on HR resources – both time and budget.

Making your HR function more employee-friendly

HR departments can significantly benefit from machine learning (ML), predictive analytics, and AI systems to assess employee satisfaction and engagement. These tools analyse various employee behaviours to gauge attitudes and identify sources of job dissatisfaction.

By examining data from several sources – such as vacation and sick leave records, performance reviews, and other workplace activities – AI systems can highlight issues such as boredom in one department or burnout in another. Such insights help organisations address problems that might otherwise go unnoticed, prompt managers to reassess their leadership strategies, and identify employees who may be ready for promotions or reassignment. 

Retaining an employee is much less costly than attracting a new one, so these methods to better understand employee engagement can help reduce turnover and the associated costs of recruiting and training new staff.

In conclusion, the integration of AI into HR practices is transforming recruitment and talent management with startling efficiency and precision. As we have seen, generative AI enhances the personalisation of job descriptions, streamlines automated recruitment processes and improves background verification – all while providing valuable insights into employee satisfaction.

As HR departments navigate this revolution, it is crucial to leverage AI’s capabilities while addressing its ethical and practical challenges, ensuring that technology enhances rather than undermines the human aspects of recruitment and employee management.

According to 76% of HR leaders, organisations that fail to adopt and implement AI solutions within the next two years run the risk of falling behind. That figure suggests those in HR are on board with the idea of AI and are already implementing it in some form because they understand the competitive advantage it gives them and the risks involved in getting left behind.

The question then becomes one about speed – whether you rush to implement AI or take your time and do so in an ethical way. In my view, choosing the latter sets you up for the long term, integrating AI solutions in a way that is both ethical and sustainable and will bring you the best results in recruitment and employee engagement.