Innovative businesses are constantly searching for ‘better’, ‘cheaper’ and ‘faster’. The application of technology to achieve this is not a new idea.
The proliferation of the smartphone entirely redefined the way many businesses interact with their customer base, and the growth of the Internet fundamentally changed the way in which many businesses work while creating new industries and professions in its wake.
Further back, robotics changed the way cars are made, the pocket calculator replaced the slide rule, the steam engine kicked manufacturing up an order of magnitude and the printing press changed the way information is spread.
Technology is continuously adopted by businesses to allow the execution of a task for less cost, more accuracy or less time. The ‘disruption’ comes when the new technology has the potential to affect a well-established process to the extent that a fundamental shift can occur in product offering, scale or cost.
The real opportunity is to allow emerging and disruptive tech to provide us with better tools, to take the time-sink, manual stuff away so that there’s more time to spend on the human part.
Just as mechanisation changed the way farming and manufacture worked by replacing physical labour, AI, machine learning and big data all have the same potential to change the way whole industries operate by replacing ‘mental labour’.
Rather than seeing this purely as a chance to replace jobs with machines, the more innovative businesses at the forefront of AI and big data adoption are analysing data far more rigorously than humanly practical to improve their processes instead.
For example, while it’s possible to spend a few minutes or hours Googling around to discover that a life assurance applicant likes to spend their spare time paragliding, a machine can collate the same information almost instantly.
Similarly, we can already see online retailers suggesting purchases based on our shopping history or (increasingly) browsing habits, which would not be a practical use of human resource in the absence of AI.
We are naturally cautious about loss of jobs to machines, but this has historically been to the improvement of overall working conditions in newly created jobs rather than us all becoming unemployed cattle controlled by a super-AI.
Indeed, the trend should be towards our tools becoming more efficient so that we all get to work a bit less hard so that we have more spare time for paragliding.
It is important not to ascribe magic powers to new technology. The most effective application of AI, machine learning and big data right now is in the replacement of manual, repetitive or analytical tasks (even if it can do them far more quickly!
The more human interaction exists in a recruitment process the more aligned an applicant is to the brand, rather than feeling ambivalent about it and reneging part way through for a ‘better’ offer.
We can ask Siri or Google to schedule reminders or show driving directions to a meeting, but they are fairly shallow conversationalists. These intrinsically transactional and repetitive tasks – and their equivalents in the recruitment process such as sourcing, searching, appointment management and CV parsing – are well suited to the abilities of AI and machine learning technologies, but things like ‘culture fit’ aren’t quite so simple.
If recruitment was genuinely as simple as matching someone’s CV to a job advert there would be no need for humans in the process already, but matching humans to jobs is no more solved than matching humans to other humans; online dating websites attempt to match people based on their attributes and personality survey answers and this doesn’t tend to work flawlessly either.
The real opportunity is to allow emerging and disruptive tech to provide us with better tools, to take the time-sink, manual stuff away so that there’s more time to spend on the human part.
If given more time to truly understand and convey a customer’s role, the humans in the process can focus on the nuanced and personal parts of the role that machines can’t.
The more human interaction exists in a recruitment process the more aligned an applicant is to the brand, rather than feeling ambivalent about it and reneging part way through for a ‘better’ offer.
A lot can happen in 10 years in tech, but things tend to take a bit longer to become standard in business.
Last year marked the 10th anniversary of the release of the iPhone and the beginning of the mass-adoption of the smartphone, and yet many companies still don’t have mobile optimised websites.
The further we look to the future, the more probable it is that the scope of AI is essentially unlimited.
Until then, we should be adopting labour saving tech and keep in mind the value of a personal interaction with a living, breathing person – in our industry, no matter how advanced AI may become, nothing will ever be as effective as the human side of the recruitment process and it’ll be those who wield technology as a tool to enhance their business practices, rather than adopt tech to replace them, who will be the leaders of the industry.
Read more about AI and Bots in our other article, Bots And The Candidate Experience.
