Recruitment industry will die in 2018.
- Published on November 20, 2016
Follow
Oleg Vishnepolsky
Global CTO at DailyMail Online and Metro.co.uk
I reckon the industry has about 2 years left in it, 4 at most. Machine learning, big data, propensity algorithms can deal with vast networks of connections much better than a human can.
The latest algorithms can predict when someone is ripe for a new job based on time in the job and social media activity, and even purchasing history.
The latest text analysis algorithms can pick out skills and experience much better than humans can, about 10 million faster.
In fact Microsoft has pretty smart algorithms in Azure cloud. They are buying LinkedIn with volumes of data and connections. Putting 2 and 2 together on what that means does not require algorithms.
Earlier this year LinkedIN bought a machine learning company with a specialty in AI recruitment: LinkedIn acquires recruiting startup Connectifier. So with help from Microsoft or not, LinkedIN is already on the way there.
Please do not take my word for it - do a Google search on automation and machine learning with recruitment. There are companies that are already doing this algorithmic sourcing. The algorithms have been used in digital marketing for years now. What is new is the maturization of the machine learning field.
There are trends in the tech industry that are harbingers of a major disruption in the field of recruitment. Technological advances can be downright cruel. We have seen whole groups of professions disappear or severely impacted: typists, clerical workers, book salespeople, stenographers, phone operators, travel agents, etc etc.
You might find these links interesting: Harvard Business Review: In Hiring, Algorithms Beat Instinct, How Machine Learning is Revolutionizing Recruiting, To all recruiters — use machine learning to hire better candidates, What Machine Learning Can Bring to Corporate Recruiting, Harvard Business Review: How to Hire with Algorithms, WSJ: Funding Snapshot: Machine Learning-Powered Recruiting Software Atipica Raises $2M Seed, 2016 will be the year of (machine) intelligence in recruitment.
Hiring decisions will still be made by people, not machines - people (internal recruiters and managers) assisted with the digital age tools. The process will be a lot less subjective and more transparent to candidates.
External recruiters will still be needed, but of different skill set - those who can deal with data and quantitative analysis, and be able to operate machine learning software. The agency of the near future will be highly digital.
A change is not necessary, just like survival is not mandatory.
I love recruiters. They are hard-working, fun-loving group of people. There are some bad apples there too who create fake jobs, do not return calls, treat candidates with prejudice and disrespect like cattle. Those bad ones give the bad rep to the industry and will get eliminated by the more efficient marketplace.
That's why I hope they are reading this, because the forewarned are forearmed.
They can begin by following automation topics in the field of recruitment. It is a good starting place.
To sum it all up:
1) Humans will NOT be replaced with robots. However, the new AI tool sets will make agencies that use these tools a lot more competitive that the ones that do not.
2) There is likely a great disruption coming for external recruiters because the technology and data provide a level playing field. The internal recruiting may not need the external agencies to the same extent as they do now. The internal recruiting will have the same tool set and data.
3) If my supposition about Microsoft's purpose of buying Linkedin is right, then LinkedIN Recruiter will provide much richer capabilities than what it does now. It would do data mining and provide a list of qualified candidates most likely to respond to an inbound inquiry. Of course, internal recruiting and hiring managers will vet this list out - hiring will not be trusted to a machine, but the process becomes a lot more streamlined. The data mining will not be just based on the resumes - it will take many other data points into account.
4) If this supposition 3 above is wrong, there are a number of start-ups already that are building and some already providing some of these capabilities today. Look at the WSJ link above as one example. As mentioned, Linkedin bought an AI company already, Connectifier.