Dec 17, 2018 | Virginia Engholm
How AI Is Helping Improve Employee Retention
AI conjures up ideas of machines controlling us and our behavior, but the reality isn’t quite so ambitious.
“There's a lot of skepticism in the market about what AI really is, largely because of the marketing hype out there on AI,” says Bill Bartow, vice president of global product management at Kronos. “People lose track of what AI really is. In fact, if you were to ask 10 people ‘What’s your definition of AI?’ you'd probably get 10 different answers.”
But AI doesn’t have to be scary. In fact, AI increasingly can help employers retain talent and prevent employee turnover.
The key to effective use of AI for retention is combining big data and machine learning with the human touch. “Be mindful that algorithms are only as smart as the people who write them,” says Kelli Dragovich, senior vice president of people at Hired. “Any company that decides to use AI to better retain and develop their workforce should ensure they have an HR team that understands the balance between relying on technology and the inherent nuances of working with people.”
Here are some smart ways employers are using AI to improve the employee experience and retention.
Better Work-Life Balance Through Customized Scheduling
Work-life balance is one of the most important factors for employee satisfaction. Employees increasingly want more say over their work time and schedule, and AI can help you give employees the autonomy they crave while still ensuring that work needs are met.
“In the scheduling arena a lot of focus is spent on making sure that employees are getting a fair, equitable, balanced schedule that meets their requirements as well as the company's business requirements,” Bartow says. Traditionally that scheduling has been done by the employer or manager generating the schedule, “but that doesn't always mean that the employee is getting the schedule that they want or need or that's best for them,” he says.
AI lets companies set up a more flexible scheduling system. “Self-scheduling — where employees pick shifts that work best for them — is becoming more and more popular,” Bartow says.
Even for non-shift workers, AI can enhance work-life balance by streamlining the process for making time-off requests, he says. “Instead of a manager spending several hours per week reviewing time-off requests — and taking days or even weeks to get back to employees — we’re using AI and machine learning handle this process,” Bartow says. These real-time time-off requests allow employees more flexibility and control over their time off while freeing up managers to spend more time on mission-critical activities.
Identifying Opportunities for Growth
One common motivation for employees is achieving goals and having access to challenging work, Dragovich says. “In fact, Hired’s latest Brand Health Report
found that 64 percent of tech workers say the opportunity to solve new problems and challenges is a top reason for leaving their current role, supporting the assumption that companies should find ways to measure how engaged employees are in their role.”
AI can be used to assess employee engagement and the quality of employee work performance, she says. “AI could provide managers with timely reminders for when an employee might be ready for a new challenge, or if they’ve outgrown aspects of their role,” Dragovich says. “Managers can also leverage AI through performance management tools such as Reflektive
to make recommendations on next steps to train their employees.”
This AI assistance can help you craft high-touch approaches to employee development and retain talent potentially at risk for turnover.
Improving retention helps increase productivity for the organization. But using AI even in the hiring process can lead to improved long-term retention, says Chris Kunze, president of Kunze Analytics
. “People that are much more fit for the job are going to stay longer because they are producing well,” he says. “They're probably being compensated better. They're being recognized. They love what they're doing. When you get a better fit person into a position, the natural outcome is greater retention.”
Small changes can also have a big effect. For example, Bartow says, consider an employee who chronically shows up late: Work is delayed. Teams have to wait for the employee to get started. Productivity is reduced.
The surprising way that AI can help starts by identifying any patterns of tardiness for an employee. “If we could predict that Bill's late every Tuesday for his 8 o’clock shift, then there's something going on in his life — maybe he's dropping his kids off at school or taking his mother to the doctor,” Bartow says. “If we know that, we can have a talk with him and say ‘Let’s find you a better time.’ ”
Ultimately AI is not about being punitive or impersonal — it’s about using data to create an environment where employees feel supported to do their best work.