The staffing industry is already somewhat artificially intelligent, and the influence of AI will only increase into the future. It could be argued that we find ourselves at a tipping point; as an industry we’re beginning to implement AI at an ever-increasing rate, and in the process we’re becoming more and more cognizant of its potential, which further accelerates its uptake.
But what does the current AI landscape look like, and how might it develop into the future? It’s a big question, and as with any that demand the use of a crystal ball, it’s one that doesn’t have a clear answer.
The current state of play does however offer up a wealth of clues as to where AI might be headed. Let's take a closer look at that trajectory, and where it might land us in years to come.
In its current form, AI isn’t a free-thinking and self-sufficient thing. It’s more of an augmented intelligence than an artificial one, as it supplements machine learning algorithms and data with a healthy dose of human input. It’s great at the minutiae, but not so good at the grand plans.
It also sees things in black and white, where the staffing industry is a rainbow of grays. An example:
On one side you have a job order that lists what an employer is looking for; things like job title, qualifications and experience that are absolute must-haves. On the other side there’s the candidate resume that lists skills, experience, and hobbies.
But drilling down further shows just how superficial job orders and resumes can be. The job order doesn’t mention things like culture fit, communication skills and career goals. The resume does an equally bad job of reflecting the human behind it; their personality, their soft skills, their hopes and dreams. In AI terms, job orders and resumes don’t offer up complete datasets, making the matching of candidate to client all but impossible.
This is why the current role of AI is limited to automating what it can, and leaving the nuance, the high value, and super skilled stuff to the human recruiter. What’s the team culture like? What personality would work well in this office? What is the candidate’s dream job? What type of working environment would get the best out of them? The recruiter asks these questions, and combines the answers with AI insights to find the perfect match.
Far from taking jobs, AI in staffing makes humans more human. You get the bot to trawl through LinkedIn, the ATS, job posts, and resumes, freeing you to concentrate on having conversations, building relationships, and elevating experiences. You can also be more strategic, choosing where to direct your energies rather than constantly chasing your tail doing prep and admin work.
AI can help with these strategic decisions too by serving up the appropriate information at the appropriate time. Imagine taking on a start-up as a new client and getting a quick rundown of its funding and organizational structure. You can check that it can afford your services, and you can gain a better understanding of the intricacies of the current role it's hiring for, and future roles it might need.
You could use these insights to blow away the hiring manager with your knowledge on your first call, and put yourself in prime position to get quality business.
So what are the factors that are currently holding artificial intelligence back? There are a number of limitations, some of which might be solvable in the near future, others that could continue to be issues for a long while yet.
There can be an ‘all or nothing’ attitude within staffing. But if you’re looking for an AI solution that can do it all, you’ll inevitably be disappointed. “The most successful businesses are those that are working to identify the individual parts of their process that AI can solve, rather than hunting for a comprehensive, end-to-end solution” notes Adam Dale, Chief Revenue Officer at SourceBreaker, a leader in Staffing AI.
There’s certainly potential for an end-to-end solution in the future, but it may be restricted to volume areas like light industrial and retail. For verticals that demand more than ‘carbon copy’ workers, there will continue to be limitations on the work that AI can take on.
Why are there these limitations? It comes back to those frustrating and ever-present grays. Unquantifiables like company culture complicate things. There are always subtle yet significant differences between companies. Take two recruiting technology firms – generally most people in this space have a similar personality and set of values, but drill down further and you’ll find that culture can vary dramatically from office to office. Everyone would happily share a drink, sure, but they wouldn’t necessarily work well for 40 hours a week together.
It’s interesting when you look at use cases and see that variation in AI matching accuracy across different industries. There is a direct correlation between the level of soft skills demanded in an industry and the success of AI matching within it. A developer is a skills-based role, making it easier to match. A salesperson is a soft skill-heavy role, making things far more difficult.
That’s not to say AI matching won’t work in those more challenging industries, but it does mean you need to be more mindful of its limitations.
We know the current situation. We know the inherent limitations. There’s just one question left to answer: where is staffing AI headed?
The limitations of resumes in representing humans and job posts in representing roles grants AI technology a real opportunity to make the industry better. The challenge will be to collect enough data to build a profile that provides a more complete picture of the human, and a more holistic view of the workplace. If we can better define vague things like soft skills and company culture, we’ll be able to use AI to match personalities to teams, not just skill sets to job roles.
AI matching software in its current form cuts the amount of potential candidates by up to 75% – where once a recruiter was faced with a list of 200, they now get a list of 50. If we can teach AI to provide a complete view of both candidate and workplace, we can cut the number by the same degree again, to somewhere nearer 10, greatly lightening the recruiter’s load, and allowing them to select from the very best fits.
How do we get there? The onus will be on staffing firms to build out these soft skill and company culture datasets, taking more notes, and capturing more data via inventive custom fields. AI could help here too. You could record interviews or source things like employer branding videos, transcribe the content, and pull out insights to better quantify the humanity of both candidate and company.
This could all lead to ‘recruiting while you sleep’. If the automated matching process is refined to the point where suggestions become incredibly accurate, a recruiter can expect to arrive at work with much of the research, red tape, and prep work taken care of. In an ideal world an AI assistant will even serve up a structured plan for your day.
This dramatic change in the way we use AI technology won’t happen on its own. It demands an equally dramatic change in mindset, says Dale.
“We need to shift to a longer-term focus. A lot of staffing agencies work in the here and now: this candidate is useful for this job, they’re placed, a record is logged in the ATS. But candidate pools need to be treated as living organisms that must be cared for, kept healthy, and made productive.”
You can’t wait for AI to come to you, and you can’t expect it to instantly solve your problems. You need to be proactive now to enjoy this automated, artificially intelligent future, and to reap the incredible rewards that it looks set to offer.