If ever proof was needed of the rise in Artificial Intelligence (AI), you could start by taking a look at the recent Budget by Chancellor Philip Hammond. Tax proposals aside, he put tech innovation, and specifically AI, front and center of his plans with over £75m of investment dedicated to AI alone.
AI still has its detractors, but it also has a growing fan base, not least when it comes to recruitment – which may be considered somewhat ironic when much of what has been said around AI in the HR and recruitment space has been ill-informed hype about robots taking over jobs of the future.
As recruitment and HR professionals embrace AI, the benefits it offers are passed on to the candidates they are dealing with. So what supports the notion that AI is increasingly helping us to find a job and, more importantly, one that we’re suited to?
In short, job searching can be pretty stressful, not just for candidates but employers too, and AI is proving to be a wonderful healer.
A large proportion of today’s job seeking population will use LinkedIn to assist with their search for the right role. If you’ve recently been part of this group, you’d have been one of 7 million ‘Open Candidates’ – people who’ve signalled that they are available for new opportunities – and LinkedIn Recruiter, the AI-fuelled tool helping employers navigate the market to find the right candidates, would have been using the data you share on the platform to try and put you in front of the right organisations for your skills and experience.
LinkedIn Recruiter uses algorithms to sift through candidates’ profiles and offer job suggestions based on patterns that have led to previous successes for similar candidate searches. The more you optimise your profile and refine your job search terms, the more accurate the job suggestions that you receive will be. With every successful match, Recruiter learns and adapts, in order to make future searches easier and more efficient.
One of the key benefits of introducing AI to job searches is the removal of ‘unconscious bias’, an ingrained human trait which results in bias towards individuals based on their characteristics.
Given the inherently objective, data-based nature of the conclusions AI offers, without the influence of experiences, prejudices and education that human decisions will inexorably have, it promises to overcome the human-driven pitfalls of traditional, manual approaches.
However, even once you’ve searched for and found a job, and successfully navigated the interview process, there’s still a key part of the jigsaw to be completed – the reference checking. It’s the final, all-important validation of everything you’ve said to sell yourself to your prospective employer.
In the UK, we have one of the poorest records of securing references – approximately only 60% of jobs have completed references. That’s probably because it’s traditionally been a slow, labour-intensive and admin-heavy process.
Automation and AI is changing that.
Take Xref, it’s a tool recruiters use that puts you, the candidate, in charge and automates reference checking to create a simpler, more efficient and secure process. It boasts a more than 90% completion rate on references – a vast improvement on traditional methods.
It also protects against fraudulent referencing activity – meaning you are no longer at risk of being denied a job because a fellow candidate has lied about their qualifications or experience to position themselves ahead of you and other applicants.
In the UK, according to Xref research, 36% of job seekers have admitted to exaggerating their work experience; 29% confessed to having deliberately lied to a potential employer; and nearly a third (28%) of candidates agree they have taken advantage of the flawed reference checking process to improve their chances of landing a role.
So the risks of an inconsistent reference checking process that lacks security and integrity are very real, but where does AI come in?
One way that Xref has applied it, to improve the outcomes of the reference checking process for users, is through the recently introduced ‘Sentiment Engine’, which uses an algorithm to interpret a referee’s ‘tone of voice’ and recognise positive, neutral and negative sentiment in the written feedback they provide.
The AI-driven tool is already delivering 92% to 98% accuracy, ensuring a greater chance of an accurate reading of your all-important references every time, without the risk of misinterpretation owing to human error or human nature (unconscious bias). Humans simply can’t compete with those stats.
It’s clear to see why AI is already a hot topic in recruitment. For both the job seeker and the employer, AI tools are making the whole process not just easier and quicker, but also smarter, with decisions based on data rather than ‘gut feel’ alone.