While recruitment technology has absolutely helped recruiters increase productivity – the uncomfortable fact remains this has often come at the cost of a much diminished candidate experience (and by default, employer brand).
Earlier this year, research from Careerplug.com found 48% of job seekers said they had at least one negative experience in the hiring process in the past 12 months. Worse still, 49% of job seekers said they had actually declined a job offer due to a poor candidate experience.
It’s not difficult to see why.
Just because it’s possible to cast a wider net doesn’t make this better.
It feels like the desire to match talent to jobs (at increasingly lightning speed) means businesses are creating KPIs that center on hiring quantity, not quality.
It’s now ‘normal’ for job applicants to never hear back after applying.
Worse still, it’s become common for companies to create a job post with no intention of hiring externally.
These things make otherwise good companies look bad. And as we all know, a bad candidate experience can turn off talent from the start, which can limit the pool of quality candidates and threaten longevity among new hires.
What makes this all the more prescient though, is with the emergence of even more technology. There is a very real danger technology will become a crutch. Yes, it will help recruiters keep pace, but it will mean they lose even more connection; creating a world where all candidate interactions are run of the mill.
When the economy is buzzing, it’s easy not to care.
But when the volume gets turned down, the expense of losing talent is much harder for an employer to ignore. The average cost of a bad hiring decision is at least 30% of an individual’s first-year salary.
The only solution is for talent acquisition professionals to scale hiring quality to match the speed that traditional recruitment technology has enabled over the last decade.
In short, it’s time to course correct TA.
Generative AI has the potential to deliver that course correction by creating a healthier relationship between hiring speed on the one hand and the candidate experience on the other.
BUT…and it’s a big but, ONLY if AI is placed in the hands of the right recruiter.
Although the large language models (LLMs) that are currently powering popular generative AI platforms are in their early stages, many valid use-cases that can improve any recruiter’s game already exist.
Recruiters who learn how to leverage the technology now can begin to separate themselves from the competition in unexpected ways.
Here are some ideas to get started with:
Biases are embedded in people and processes everywhere.
Unconscious bias in recruiting can negatively impact how companies make hiring decisions and how employer brands are perceived by prospective talent.
If unchecked, bias can cause unintentional damage by reinforcing harmful stereotypes for job applicants and candidates or tarnishing the reputation of a recruiter or employer.
Recruiters can use AI-powered writing-enhancement platforms to minimize bias, using the technology to remove human subjectivity from every text-based candidate interaction.
For example, a recruiter can run a job description through a generative AI tool, asking it to identify biased language and provide suggestions for more inclusive alternatives. This process can also be implemented to ensure language that is inclusive and non-harming across the board, including in the creation or editing of career site copy, benefits lists, defining career paths, or for recruitment-centric social media posts.
With AI-assisted communications, recruiters may have more confidence engaging with talent (such as those from underrepresented groups) who have come to expect a disappointing experience from employers. This could help companies earn access to untapped talent markets as an employer of choice.
It’s already happening: In March LinkedIn announced it was testing AI-powered job descriptions, leveraging an advanced OpenAI GPT model.
Candidates are often interviewing with more than one company, being asked the same questions, and faking enthusiasm while delivering the same, acceptable responses every time.
Ask a candidate what their greatest weakness is and you’ll get a dispassionate, recycled reply (likely copied from management consultant “influencers” on TikTok or LinkedIn).
Why let this happen? Interviews should instead be a defining moment in the candidate experience — not only to qualify their job skills and cultural fit, but to build the beginnings of a positive relationship between the company and a future employee.
But a great interview requires asking the right questions. This is where generative AI can also help.
Use generative AI to produce interview questions that are tailored to the specific job opening in question and to a candidate’s potentially unique or differentiating qualifications.
Additionally, AI prompts can be optimized to ensure the interviewer gets more useful insight into each candidate’s “soft” capabilities, such as social skills, leadership potential, or approaches to teamwork.
And, AI can do this fast. If fed a summarized job description, generative AI can produce an entire, personalized interview guide for any role in a matter of seconds.
After interviews are completed, a number of AI tools can be used to surface the most important parts of any conversation, by nearly instantly summarizing notes or even a recorded video, to ensure highlights are not overlooked when comparing candidates.
This can be valuable to help make a hiring decision, especially when multiple stakeholders are involved, or to provide meaningful feedback to a candidate that didn’t make the cut.
Personalization is the key to making candidate outreach and engagement meaningful.
Yet until very recently, the industry standard has been to send the same email blast to hundreds of candidates and cross your fingers. That approach won’t cut through the noise today.
Some recruiting platforms have begun integrating generative AI tools, such as GPT-powered text generation features, to help recruiters scale personalization without losing speed.
Right now, these features are primarily built to support candidate outreach. For example, in as little as one click, recruiters can take a target list of candidates and auto-generate an opening message with human-like text, including relevant information about the candidate and why they may be a good fit.
You know how it’s always a little shocking when a cold email from a salesperson actually feels like they’ve done some research? Imagine every candidate you email feels that way when reading yours.
When used correctly, AI-supported outreach can help recruiters greatly reduce the effort spent on an effective intro, so that they spend more time on quality conversations with candidates that show interest.
What I’m not saying is that recruiters should apply a few new layers of automation to their existing process and calling it a day.
That mindset will only lead to more of the same that got you here — low-quality engagement and a dull candidate experience.
Instead, it’s time to get comfortable enough to tinker with new tools that can help you improve your game.
That’s why generative AI should be leveraged in new and creative ways to reduce the time recruiters spend on repetitive tasks, to create the opportunity for a stand-out experience.
To add to your own exploration, there are free online learning courses on generative AI for recruiting already available.
I haven’t even scratched the surface. But diving in early to use AI for recruiting in these ways is what putting this technology in the right hands is all about.
