While artificial intelligence remains a sometimes-sinister specter in pop culture, the corporate world is betting its future on the technology. AI applications are cropping up across multiple industries, especially in human resources.
Turns out there’s a major need for AI in HR. According to a 2016 survey from workforce analytics company Visier, 70 percent of hiring managers agree that recruiting programs need to utilize more data to improve the long-term business impact of hires. As such, many companies are integrating AI’s data processing capabilities into their recruiting methods with one goal in mind: find better candidates, faster.
Unlike keyword-crawling solutions of the past, AI can draw more complex insights out of candidate data, making sense, for example, of job titles that don’t match the company’s corporate structure by cross-referencing external data points about titles (including relevant skills, salaries and experience levels). AI can also connect data across networks, combining a candidate’s resume with their digital footprint to create a more holistic profile. These applications are unburdening HR departments in industries from finance to consumer goods. And like any employee, the more training AI gets, the better it performs.
Today, AI’s applications in HR are focused predominantly on the beginning of the recruiting process: candidate sourcing, resume screening and interview scheduling. AI can evaluate and analyze data in a fraction of the time it takes recruiters to do the same.
“Where companies find the most value are efficiency metrics,” says Ji-A Min, head data scientist at Toronto-based recruiting software company Ideal. “Instead of spending dozens of hours on resumes, you can get that to seconds and minutes.”
Many companies have so many incoming resumes—or such a small HR team—that they often don’t process most of them. By setting AI to the task of resume screening, HR departments don’t overlook anyone interested in or qualified for an open position. And as AI assumes tasks like candidate screening and scheduling, HR employees have more time for things like conducting interviews. While AI can’t yet conduct interviews, its ability to discover and recommend more qualified candidates means the rate of hires per interview increases threefold, according to Ideal.
AI Needs a Data Network
The state of AI in HR is similar to the state of AI in most industries right now: there’s still work to be done. For HR, recommendations will likely improve as the technology’s network of data points grows.
“We’re in the data-training phase with AI,” Min says of the technology’s progress in the field.
Jana Eggers, CEO and co-founder of Boston-based AI company Nara Logics, says the availability and sophistication of hiring data will increase as more companies adopt AI in their HR departments. If AI knows not just where an employee worked in the past, but also what qualities and skills helped that employee succeed at those companies, it will be more equipped to identify top candidates. The same goes for education data: rather than looking only for applicants from top-tier schools, AI can make recommendations knowing what qualities and aptitudes candidates from certain institutions often possess. The more specific all of this data is, the better, says Eggers.
Eggers points to her team’s work with a New York-based nonprofit as evidence that a thorough network of data can make AI more effective. The nonprofit works to match entrepreneurs with mentors for career development, and with data about both the mentors and entrepreneurs—their backgrounds, areas of expertise, schools, personal connections—Nara’s AI found better matches, faster. The AI also contributed to new discoveries: many of the entrepreneurs and mentors had attended the same events —a data point the company hadn’t originally considered, but one that helped make more relevant matches.
As AI continues to collect talent data, its applications will grow, extending beyond hiring and across the entire employee lifecycle including retention, training, performance and productivity.
“Before, we were constrained by data we could collect in a human way,” Min says of the promise of AI in HR. “Now, these technologies use their AI and machine learning to analyze and collect data in ways we couldn’t. There are some insights that AI [gives] us that we haven’t considered.”