A Resource for Employers
How AI & Machine Learning Can Help You Hire
The rise of Artificial and Machine Learning technology is transforming how we conduct business — and the same is true for how we attract and hire talent. But how exactly can employers and recruiters leverage this new technology and make the most out of our new machine-empowered world?
What is Artificial Intelligence (AI)?
AI is a system that aims to emulate the natural intelligence of biological lifeforms in computing. Any system that can perceive its environment, understand inputted data, and execute actions based on analysis has artificial intelligence. Typically, this involves problem solving and learning from new data, adjusting conclusions in line with new data. Until recently, IT systems have been incapable of this.
It’s probably simplest to think about today’s AI as being able to simulate thought processes, rather than an entire thinking mind (let alone a computerised super-genius). Due to the limited capabilities of today’s technology, you won’t come across any thinking machines just yet.
What is Machine Learning?
While at first AI and Machine Learning appear similar, there is an important difference. The term “artificial intelligence” describes how a machine comes up with the answer or response to a given input. Machine Learning describes how a machine acquires the knowledge to base those responses on.1 The code explicitly instructs the system how to learn.
Where conventional coding tells an IT system what to think and do, Machine Learning instructs a system on how to think and act.2
How can AI and Machine Learning improve the recruitment process?
Today’s hiring environment, with its large amounts of digital data, is ripe for AI and machine learning-based optimisation. Each stage of the hiring process offers opportunities to use technology to automate, optimise and audit the procedures used to select candidates.3
However, it’s possible to hand too much of the process over to computers. A recent study showed that many candidates are put off by too much automation in the hiring process.4 The best way to get around this is to take full advantage of AI and Machine Learning towards the beginning of the recruitment process, moving to a more personal touch as you start to narrow down the field of potential recruits.
Planning and Market Analysis
In the initial planning stages, AI can help recruiters match and standardise skills, experience, knowledge, and job requirements for a given role. There is evidence that AI-powered recruiting software used in this way increases productivity by 4% and reduces employee turnover by 35%.5
AI-powered chatbots can be a big help when trying to attract the right candidates. By pre-programming a lot of the information people commonly ask for, you get the chance to build a rapport with potential recruits before they every apply.
AI and Machine Learning are both fantastic technologies for automatically processing large amounts of data. Being able to filter out the right potential recruits from a large pool of potential candidates can save you a lot of time and hassle. Using AI to screen candidates is also great for removing unconscious bias, or making sure you don’t miss anything whilst wading through piles of applications.
Automated candidate sourcing can be used to scrape social media sites for those hard-to-fill positions, and for the rediscovery of applicants for similar positions. Candidate matching can also help eliminate applicants who don’t meet your needs, whether that’s due to skills, experience, or other factors.
Tired of asking the same old interview questions? AI can help you produce a set of interview questions that’s tailored to each candidate. In theory you can automate the entire interview process, though in practice this isn’t popular with candidates.
Post-interview, it’s possible to use AI to analyse a recording of the meeting. This can help you gain insights on everything from a candidate’s truthfulness to their attitude towards their previous employer. Facial expression analysis has come a long way in the last few years, and at the same time recording interviews has also become more commonplace.
There are a few different ways AI can support the final selection process. This is especially helpful when you have several strong candidates with little to choose between them. By going back over the final few candidates with your selection software, you can extract enough data to be able to choose between them.
Personalised onboarding plans are the way of the future. You can concentrate on the areas where the new recruit needs the most support or input to be able to do their particular job well. This is also a chance to get additional data to feed back into the hiring process for future applications.
What to do with all of that data now you’ve made your hiring decision? Make the most of what you and your machines have learned, and use data about the chosen candidate, their performance, and more to help support future hiring cycles.
The additional data gathered when you adopt AI and Machine Learning gives you the opportunity to find out whether your hiring practices genuinely lead to good employees. This is something that few organisations do, so making use of this data to improve your procedures will put you ahead of your competition.
AI and Machine Learning are here to stay, and they’re already having a big impact on how organisations recruit new employees. Used correctly, these tools have the potential to improve your hiring process and give you insights into many aspects of your company’s job roles.
Start using AI and Machine Learning today, and see how it can help you build the best possible hiring process for your company.
- Stanford Encyclopedia of Philosophy (n.d.), Artificial Intelligence
- DeMuro, J. (2018) What is Machine Learning?, Tech Radar
- Glassdoor (2019) 7 Steps Every Recruiter Should Follow
- Wright, J. and Atkinson, D. (2019). The impact of artificial intelligence within the recruitment industry: Defining a new way of recruiting. [online] Cfsearch.com.
- Ideal. (2019). AI For Recruiting: A Definitive Guide For HR Professionals.