Will AI take the “Human” out of Human Resources?

So far, this has been the year of AI. There isn’t a single field that isn’t researching how they can use AI tools to make their employees’ lives easier. The HR community is no different. There are hundreds of blogs and articles about different AI tools and their uses within HR. 

However, there’s also no field of work quite like HR. “Human” is literally in the job title. The role of an HR professional, whether they specialize in recruiting, company culture, or employer branding, always returns to providing the best experience for the people working for the business. 

Do AI tools put HR professionals at risk of turning their jobs into a numbers game? Are machine learning models compatible with DEI efforts, or will they undo years of hard work? 

In this article, we’ll discuss some of the ways that AI can support HR professionals while highlighting what you need to be aware of before implementing a new tool. 

AI for Recruiting 

Out of all the branches of HR, recruiting is probably the specialism that has most quickly adopted AI. 

This makes sense – first, during active recruitment, recruiters often have to search for good candidates in a never-ending pool of talent. Knowing which individuals make good employees requires a huge amount of knowledge about every department and role they are recruiting for. AI tools such as Celestial.ai can build lists of suitable candidates for roles based on LinkedIn or job board profiles. 

Meanwhile, some large organizations receive hundreds, if not thousands, of applications for roles. Filtering these down to a manageable number for first interviews and assessments takes a huge amount of time. Many firms use AI tools like Ideal to read and filter out CVs that don’t meet certain requirements. 

There’s also a large amount of administrative work associated with recruitment. Candidates are more likely to accept offers when they’ve been regularly contacted by their recruiter, and when they’re given plenty of information about onboarding at an early stage. Many recruiters are using AI chatbots like Olivia to automate this process. That way, candidates feel like they’re being taken care of throughout the process, and they have a way to ask further questions.  

The Problems with Using AI for Recruitment 

One of the ongoing discussions within recruiting is how to eliminate as much bias (conscious and unconscious) as possible from the process. Some changes are simple and practical, like removing names and photographs from applications. Others involve getting more feedback on an application or setting skills-based assessments that add balance to the process. 

When using an AI tool to filter or scout for candidates, one must be aware that the model may have been trained on existing industry data. That means, in an industry where men are over-represented, for example, it might suggest more male candidates because that has been the historical pattern. Alternatively, it might promote people with degrees from certain universities, which means that many high-quality candidates with a different background will be overlooked. 

There need to be checks and balances when using AI to support recruitment. HR teams need to regularly review rejected CVs to check that the software isn’t rejecting qualified candidates by accident. When machine learning models are trained using historical data, you need to be careful that it isn’t helping you to replicate existing biases. And it’s always important to remember that each CV that lands in the rejected pile represents a real person who deserves to be treated fairly. 

AI for Employee Development & Education 

Another area that is adopting AI is the employee development and education sector.

In this case, Learning Management Systems (LMS) integrate AI to identify an employee’s individual strengths and weaknesses. They can then build programs that are tailored to them. Rather than all employees receiving the same training, these programs can focus on their weaknesses, revising items that they didn’t understand on the first try, and revealing new material once they understand the basics. 

This software can also be useful to HR managers looking to identify talent within their company. Employees who signal their interest in a new area via learning tools can be directed to apply for internal vacancies. Alternatively, employees with great leadership potential can be identified and nurtured. 

Risks of Using AI for Employee Development 

Tools that use AI to support employee development often use very standardized methods of testing. They conduct online training alongside quizzes or exercises that are marked centrally, with the result being a set of numbers that can be compared to the results of other employees.  

One risk is that these kinds of training programs don’t work for all kinds of learners, and therefore some employees will find them more enjoyable and easier than others. It’s also not advisable to rely on assessments for identifying potential leaders. They can be useful additional data points but may not accurately reflect what an employee is delivering for a company. 

AI for Employee Experience & Company Culture 

AI tools can be extremely helpful for People & Culture departments as well. 

For example, a tool like LumApps automates and customizes internal communications. Their conversational search feature makes it easier for employees to find information on workplace policies, internal knowledge bases, or other frequently asked questions. Employees also receive a personalized content feed that includes content from relevant colleagues or departments. This can contribute to a collaborative and open company culture. 

Meanwhile, tools like Semos Cloud help managers to automate employee recognition and deliver rewards or shout-outs in a common digital space. It also administers and analyzes data from employee surveys, so that People & Culture teams have more insight into the status quo without having to process the data themselves. 

What to Consider When Using AI for Employee Experience 

As with AI tools for employee development, employee experience tools tend to simplify results into numbers that are easy to digest and compare. As a result, you can lose the qualitative data that is so valuable in the People & Culture space. 

For example, it’s not enough to know that people are 10% less likely to recommend the company as an employer in Q2. You need to know what has changed since Q1 and what is currently happening to create the trend.  

Another potential downside to using an AI tool for internal communication is the same as using any other virtual format – employees usually have the option to turn off notifications and are likely to do so if they feel the content is a distraction rather than helpful. AI tools for internal communication won’t solve all of your problems but are an additional channel, albeit one that needs less active management. 

AI Tools for HR – Choose Carefully & Monitor the Impact 

This article only scratches the surface of how AI is changing HR. There are dozens of ways that technology can reduce administrative burdens and streamline processes – and we can and should celebrate that. 

However, HR professionals are usually drawn to their roles because they have an affinity for people. If new HR tech continues to turn employees into numbers on a page or rejects excellent applicants based on data analysis alone, then it’s overstepping its mandate. 

AI will be an incredibly powerful tool for HR. AI-based tech should free up HR managers to spend more time with their company’s employees, rather than anchoring them to a screen. It should support HR managers in delivering more customized and thoughtful initiatives. However, those selecting and implementing tools should be cautious during the test phase and maintain awareness once the technology is live. After all, a technology that is continuously learning could get into bad habits if left unsupervised.