Lorem ipsum dolor sit amet, consectetur adipiscing elit. Vivamus convallis sem tellus, vitae egestas felis vestibule ut.

Error message details.

Reuse Permissions

Request permission to republish or redistribute SHRM content and materials.

The Role of AI in Retaining Top Talent

Two business women shaking hands in a meeting room.

​The ability to retain top talent is top of mind for employers, HR professionals, managers and supervisors in companies of all kinds across all geographies.

As they frantically struggle to find reliable fixes that can help them minimize talent loss, potential relief may be available from a solution they might not have considered—artificial intelligence, or AI.

One of the things that research tells us is highly important for employees is the ability to grow and develop. If they can't do that within your organization, they'll look elsewhere for these opportunities. AI can help you ensure that you're not overlooking employees who are poised to move on to bigger and better responsibilities.

"People stick around longer when they have opportunities for career growth," said Janet Clarey, director of HR research and advisory services at McLean & Company in London, Ontario, Canada.

She said McLean & Company has found that "employees who agree or strongly agree that they can advance in their career in their current organization are 3.4 times more likely to be engaged, compared to those who disagree or strongly disagree."

Organizations can use AI, she said, "to algorithmically match people with internal opportunities such as project and gig work, full-time roles, learning experiences, and mentorships based on that person's individual skills, experiences and interests."

AI technology can also help companies allocate work most effectively and efficiently—making sure the right people are working on the right things and improving the odds that they will be engaged.

"Automating routine tasks like filling timesheets at scale has many advantages aside from merely monitoring the in and out time of employees," said Lakshmi Raj, co-CEO and co-founder of Replicon, based in Redwood City, Calif. "They can use data to find the best fit for projects, augmenting the quality of output by utilizing their resources optimally." Doing so can also minimize the potential for burnout, she said.

Preventing Burnout

Janelle Owens, SHRM-CP, is the HR director at Test Prep Insight. She said her company is "using behavioral analytics software to identify burnout among key employees before it happens in an effort to reduce churn." Burnout can be a big driver of turnover. Fortunately, she said, "behavioral analytics can provide key insights into employee behavior and help prevent burnout before it gets to a breaking point."

Test Prep Insight has used AI-driven software since the onset of the pandemic. "This software gathers and analyzes employees' communications through existing channels like Zoom, e-mail and Slack," she said. "It then identifies trends and certain buzzwords in their messages, running this data through its algorithm to identify at-risk employees." That's been especially important in a remote work environment, she said.

"One of the ways to arrest employee burnout is to identify resources that are overutilized and underutilized," Raj said. "With AI and machine-learning-based professional services automation and cloud-first time-tracking solutions, enterprises can analyze real-time data to enable more effective allocation of resources, ensuring balanced workloads, high employee morale and reduced attrition."

Identifying Employee Flight Risk

"Using both internal and external data, AI can be used to build predictive models of employees who may be a flight risk," Clarey said. Some examples of internal data are job satisfaction, number of positions held, engagement score and years with an employee's current manager. External data can also be used—for example, benchmarking compensation rates by tenure.

Omer Usanmaz, CEO and co-founder of Qooper Mentoring and Learning Software, said other data that can be used to identify patterns that may indicate an employee is at risk of leaving include "how often employees are logging in, how much they are working, how engaged they seem in their work and how often they are interacting with co-workers."

In addition, Usanmaz said, natural language processing algorithms can be used "to analyze employee communication data—this could include analyzing the content of e-mails, chat logs and social media posts in order to identify signs that an employee may be considering leaving."

However, Clarey cautioned against using AI to predict what individuals might do. "There is a large amount of uncertainty in predicting whether an individual will leave, but when you apply that prediction across thousands of employees, the accuracy will increase dramatically," she said. "So, for example, these predictions should be used to inform workforce planning on an organizational level, not to prepare to replace an individual because the algorithm says they're a high flight risk."

There are also some other important caveats companies should be aware of as they consider the role AI could play in helping to retain talent.

Some Stipulations

One possible concern, Owens said, is the potential for causing anxiety among employees who may be worried about employer monitoring. However, she said she's seen studies indicating that "62 percent of employees say they are not worried about employers monitoring their behavior." And, she added, "employee monitoring has sort of become the norm, especially during the pandemic."

Still, when using this kind of technology, it's important for employers to be upfront about why and how they're using it and respond to employees' questions or concerns.

In addition, Usanmaz said there is the potential that employees may try to "game the system." For instance, if they're aware that their data is being analyzed in a certain way, they could, potentially, artificially inflate their engagement or hide their intention to leave.

When it comes to preventing turnover, the bottom line is that "even the best AI in the world gives you an incomplete picture of turnover," Clarey said. "There is an unpredictable, human element to turnover that can only be understood by managers and leaders, who, when engaged and involved with their employees, can predict the unpredictable." It is, she said, the combination of data and human intuition that leads to successfully reducing turnover.

Usanmaz pointed out that, most importantly, companies should "focus on proactively retaining employees by creating a positive work environment, offering incentives and rewards, and providing opportunities for growth and development." He said it's important "to keep open communication with employees to ensure that their needs are being met and that they feel valued in their position."

Lin Grensing-Pophal is a freelance writer in Chippewa Falls, Wis.


​An organization run by AI is not a futuristic concept. Such technology is already a part of many workplaces and will continue to shape the labor market and HR. Here's how employers and employees can successfully manage generative AI and other AI-powered systems.