By automating some of the more repetitive recruitment tasks, companies are seeing the potential to make the process of finding, screening and onboarding candidates quicker and easier than ever before. CNBC has suggested that almost all of the Fortune 500 already use some kind of automation in their recruitment process.
AUTOMATION VS ARTIFICIAL INTELLIGENCE
The key word here is automation. We’d say that the difference between automation and true artificial intelligence is the Machine Learning element. True AI requires the computer to learn and essentially make judgements in the way that a human would, evolving its algorithms through experience, in the same way that we evolve our behaviours.
HOW AUTOMATION IN RECRUITMENT IS SPEEDING UP CANDIDATE SCREENING
The start of any recruitment process is labour intensive, with recruiters either experiencing a dearth of candidates (usually in highly skilled or emerging fields) and needing to source more, or finding their desks buried under a tsunami of CVs waiting to be screened.
The opportunity to automate these labour-intensive early stages of the recruitment process definitely has its appeal.
The technology is now getting to the point that harnessing machine learning and artificial intelligence for the initial screening of candidates could substantially reduce the administrative burden faced when application levels are high.
Artificial intelligence in recruitment can enable more CVs to be reviewed, faster, making it quicker to identify those with the right experience on paper. It’s possible that AI could even extend beyond creating the initial longlist, to analysing and even interviewing and shortlisting candidates.
HOW COMPANIES ARE USING ARTIFICIAL INTELLIGENCE IN RECRUITMENT FOR FAIRER CANDIDATE SCREENING
In some companies, recruiters are turning to automation to remove long-ingrained biases that are no longer important to that particular institution or business. As AI advances, more and more biases will be addressed. These biases could be a pre-disposition to an alma mater, or a bias based on physical appearance.
With the correct algorithms driving artificial intelligence, results can be driven purely by the right qualifications and skill sets. In principle, this should give all eligible candidates a fairer chance in the process.
AI AT IC RESOURCES
Whilst automation and next-generation AI in recruitment most definitely offers new opportunities around meeting candidate quotas and achieving headcount targets, here at IC Resources we don’t envisage AI as being a key enabler for ourselves or our clients in the foreseeable future.
We already use automation via advertising platforms – LinkedIn will send job listings to suitable LinkedIn members and job boards will highlight relevant CVs. However, we still need to search outside the ‘standard’ parameters set by these automated systems, because they are not nearly sophisticated enough to replace the flexibility and insight of the human brain – especially a human brain which is an expert at recruiting in a highly specialised technical domain.
The process of then screening CVs and interviewing candidates on behalf of our clients then becomes our priority. AI could reduce the number of CVs screened according to certain criteria, but we’ve learned that you can’t be constrained by the criteria on a job description. For example, a role might ‘require’ 10 years of experience – an easy qualifier for AI. But what happens when someone with 3 years of industry experience has also been programming software at home since the age of 15? Suddenly 3 years of experience becomes 10. In our view, it will take many, many years before such judgements can be made by artificial intelligence.
What’s more, this is the most basic type of judgement. There is no AI that will identify whether a person is the right cultural fit for a startup, or whether their wife/husband/partner is going to veto a job move or a location move at the 11th hour!
There’s only one way to offer a genuine ‘value-add’ service to busy and ambitious clients. Consultants need to have an awareness of the client culture, the job, the market, the network and the candidate pool, and then consider the suitability of individual candidates in their entirety – as people in their own right rather than a ‘product’ that can be analysed through machine automation.
Recruitment isn’t about the fastest way to sift CVs, but a much longer path that starts with understanding exactly what skills, experience and personality traits business managers need and ending only once the candidate is settled into their role.
There is, without doubt, an opportunity for artificial intelligence in recruitment, and the use of big data to support the essential role of consultants in recruitment services; helping them to become more knowledgeable about their markets, especially niche or evolving markets. However, artificial intelligence still has a way to go before it becomes a serious long-term alternative to experienced consultants working with candidates to guide them through one of the most stressful and important decisions in life.