Artificial intelligence and machine learning continue to streamline HR processes, enhance decision-making, and develop employees. What’s next?
On any given day, the number of muffins a Costco store sells can vary wildly. This variability made bakery staffing needs hard to predict. Schedule too few employees, and customers might not get the baked goods they want, but over hiring and overstaffing results in extra costs (and leftover muffins). It’s a problem common to many perishable products, although baked goods are especially prone to waste.
In search of a solution, starting in 2018 Costco tested using a machine learning model to predict the number of bakery products needed each day. Trained on historical trends, the model considered numerous factors, such as weather and local sporting events. Success followed: the 30-store pilot project reportedly resulted in nearly US$100 million in savings and has since been adopted company-wide.
Costco’s work highlights two underappreciated aspects of the use of artificial intelligence (AI) and machine learning (ML) in human resources (and, by extension, the operational work HR helps to supply).
New AI tools are impacting HR
First, AI is, of course, a lot more than just ChatGPT and its ilk. Conversations about generative AIdominate the media right now, but HR applications of machine learning predate generative AI and are often more advanced at this time.
Second, both AI and machine learning can be used in ways people have hardly considered yet. Even though its application is already widespread—the research firm IDC estimated that in 2023, 60% of the world’s largest businesses would use AI or machine learning “to support the entire employee life cycle experience”—and as the technology progresses, HR will use these tools to address an even wider range of tasks and challenges. These complex, iterative mathematical algorithms can recognize patterns and predict future developments, providing useful insights for HR professionals that touch on almost every aspect of work.
Hurdles remain: employee and candidate privacy requires protection. AI is susceptible to bias, depending on a raft of factors, from the underlying data sets—to the people using the tools. And without the right transparency, testing, and guardrails in place, many potential uses of AI will run into workforce resistance.
But the promised benefits make a compelling case for overcoming those hurdles. Here, we look at progress in current and potential uses in key areas of HR responsibility, from talent acquisition to training to succession planning, as well as how top companies are working to apply AI and machine learning in a trustworthy way.
Talent acquisition: scoring candidates, spotting adjacent skills
Talent acquisition is an exercise in pattern recognition, finding individuals with certain skills and interests and connecting them with jobs that match. This is especially important now, as technology is rapidly changing the work environment, making certain jobs obsolete while creating a demand for new roles that require new skills. This makes it a natural area to apply AI/ML. In fact, 2023 research by SAP SuccessFactors finds recruiting is the number one HR area organizations are currently investing in, with uses including:
However, these possibilities immediately surface the concerns about AI that HR must address. Hiring is particularly susceptible to AI bias. Any AI is only as good as the data it’s trained on, and various headlines in recent years—from an Amazon recruiting tool biased against women candidates in 2018, to a 2023 lawsuit alleging racial and age-related discrimination in Workday’s screening tools—can give pause to both candidates and employers.
Furthermore, employees are most comfortable with intelligent technology accessing work-related data sources, such as work calendars, active status, time tracking, and e-mails. They are least comfortable with technology accessing data related to their physical body, such as their tone of voice, eye movement, body language, or facial expressions.
To address these concerns, some states are introducing or considering laws related to the use of AI in hiring. For example, as Bloomberg Law reports, New York City’s Automated Employment Decision Tool (AEDT) law, effective July 2023, requires employers that are using AI and other machine learning technology in the hiring process to conduct annual third-party audits of their recruitment technology. Failure to comply with the AEDT law could result in fines of up to $1,500 per instance.
