61% of recruiters expect hiring volume to increase this year, but recruiter headcount is expected to be relatively stagnant. As a result, there’s an even greater need for better candidate sourcing tools in 2018.
But which candidate sourcing investments make the most sense for you? Here’s my guide to understanding how AI is improving candidate sourcing tools in 2018.
Candidate sourcing: where is recruiting headed?
Recruiting increasingly needs to become a strategic advantage.
It’s true that automation will eventually fully get to scale and potentially eliminate million of jobs, but that’s still decades away. Today, people power organizations and having the best people makes the best organizations.
Unfortunately, the popular phrase “war for talent” has become “the war on talent”:
Instead of winning a war for talent, organizations appear to be waging a war on talent, repelling and alienating employees more successfully than harnessing their skills. The result is a highly inefficient job market where most companies complain about their talent shortages while most employees complain about their pointless jobs.
There are numerous reasons why this happened. One of them is that recruiting is usually through HR, and HR isn’t directly revenue-facing. As a result, decision-makers haven’t cared about it as much as they should in the past.
The other reason is that there’s often a poor alignment between where recruiting is headed technology-wise and how organizations are structuring their recruiting function.
This is what many companies can make improvements.
Candidate sourcing tools need to reflect the future of the tech stack
Here’s what you need to consider in your candidate sourcing process:
- A way to automate some of the rote functionality of recruiting
- A way to design a better candidate experience
- A way to reduce bias
- A way to interact better with self-selecting candidates
If you could do these four things, you’d probably be pretty far ahead of the pack in terms of your recruiting function.
So, how do you do that?
Improving rote functionality with AI sourcing tools
Why would you want you (or your recruiters) doing rote task work when they could be doing more strategic, relationship-building work?
And what if you could do this and reduce time to hire from 34 days to 9 days?
You can do all this. It’s called artificial intelligence for sourcing.
How about improving candidate experience?
Start by thinking about the various frustrations that candidates have with the existing recruiting process.
Most of these come back to communication in some way:
- They never know the status of their application
- They apply for one job, get decently far in the process, and don’t get it; months later they see a similar job at your company and have to start from scratch
These flaws are usually the result of tech problems and time management.
If your internal team doesn’t have the time to communicate with candidates about their status, use a recruitment chatbot.
Is it slightly less human? Yes.
But lack of communication is the biggest complaint of candidates, and if you want to solve for it, you need to use more effective tech.
The second problem is related to candidate rediscovery and it’s also a tech issue at heart. Most conventional Applicant Tracking Systems (ATS) don’t learn as they grow and they can’t contextualize.
This is why resumes enter what we like to call “the applicant black hole.” There’s no way to access information on past candidates easily and accurately.
Rediscovery is different from keyword or boolean searches because it uses AI to learn the requirements of the role and then scans resumes to find candidates with matching qualifications.
No more black hole. Better candidate experience. Your brand wins. You get better people faster and with less effort.
Reducing bias with AI sourcing tools
Artificial intelligence also helps reduce bias, in large part because it makes decisions based off data points.
Recruiting AI sources and screens candidates by using large quantities of data. It combines these data points to make predictions about who will be the best candidates. The human brain just can’t compete when processing information at this massive scale.
AI assesses these data points objectively – free from potential biases by ignoring demographic information about candidates such as their race, age, and gender in its decision making.
With more and more AI-powered candidate sourcing tools available in 2018, organizations have a massive opportunity to make some concrete improvements to their recruiting efficiency and candidate experience.