AI candidate experience, that is using AI to influence or complete a large number of candidate facing interactions, is all but a settled matter at this point. At the recent Talent42 Conference in Seattle, Head of TA for Datavant, Dan Cambell, noted that an estimated 400,000 recruiting jobs will be lost in the coming years. Lost to AI in one form or another.
The need for traditional recruiting staff will be reduced both by AI automation of recruiting tasks and reductions in the labor force due to AI automation of myriad positions that currently require human support. Fewer employees means fewer open jobs which means fewer recruiting resources required.
The shift has already started to a small degree. The popularity of recruiting bots and conversational chat over the last few years was the first salvo. So far, and for the foreseeable future, AI candidate experience appears to be the focus. The question is, will these experiences be positive or negative?
Pros and Cons of AI Candidate Experience
My best guess is that AI based candidate experiences will (and do) range from awful to acceptable. Especially over the next few years. To be fair though, many employers already provide awful to acceptable candidate experiences with no assistance from AI.
So far, the candidate facing AI offerings perform tasks like answering questions, scheduling interviews and coordinating tasks associated with recruiting processes, most of which affect candidate experience.
That said, these tools appear to be only a mild upgrade from rules-based systems, performing the same tasks at this point. In some cases, these AI tools are more rules based than AI based, but that’s a different subject.
The immediate benefit of AI candidate experience is short term cost savings. Organizations can leverage knowledge bases more elegantly and answer non-specific candidate questions or complete tasks more conversationally. I would guess that recruiting knowledge bases for the majority of employers need a lot of attention at this point. But with all the hype around AI, it’s a safe bet that organizations will sort out and properly deploy these knowledge bases, whereas it may have been a lower priority in the past. The industry, the world, is looking to invest in future cost savings with AI.
These knowledge bases can be utilized for chatbots, email responders, scheduling and requisition management to not only execute tasks but add value to the task. There should come a time when an AI agent can scour talent acquisition emails and create its own knowledgebase. And whatever knowledge repository it uses will get better and more complete as the agent understands the tasks and the content. The future of candidate experience with AI is indeed quite exciting.
As for the “cons,” maturity is up first. As I said, it’s early days for AI tools and in many cases they deliver little functionality beyond similar rules-based technologies. Another con is the regulatory environment. Sure there will be a short term efficiency to routing and answering general questions about jobs, the company and the hiring process, but candidates want information about their specific situation. And that would require putting large amounts of very sensitive data into a model. The risk of data leakage and misuse, along with the potential legal ramifications of candidates claiming that their AI interactions affected the hiring decisions, all make widespread adoption of truly personalized AI candidate experience tools a slow undertaking.
Governments are already gearing up for regulations surrounding technology transparency in AI matching and assessment technologies. I see no reason why the discrimination risk wouldn’t extend to day to day interactions with candidates.
But all this is mostly in the future. The very near term con of AI candidate experience is the very real risk of unseen and unknown problems leading to bad experiences that affect hiring effectiveness.
Trust But Verify Your AI
Employers have already deployed numerous AI and/or rules based recruiting tools that directly affect candidate experience over the last few years. While correlation is not causation, I can’t help but point out that candidate resentment is at an all time high these days.
Employers should absolutely gain efficiencies wherever they can. And as they deploy agents, bots and associated AI that touches candidates, it is crucial to understand the effect that these tools are having on candidates, as well as what issues they may be introducing into your processes.
Some AI tools provide basic satisfaction feedback after interactions, but a thumbs up or down gives you no indication whether you’re introducing first order or downstream problems with your recruiting processes. And they certainly don’t surface what those problems might be.
Tools like Survale identify issues with technology and process and surface specific, actionable insights to optimize them every day. If a candidate is unsatisfied after an interaction with an agent or bot, knowing exactly what happened and why it happened is crucial. Especially in these early stages of adoption. Thinking you know what’s happening with candidates and technologies and processes is simply not a good strategy while automating candidate experiences in such transformative ways. Employers need strong tools to understand exactly how AI is affecting candidate experience and overall hiring effectiveness.
