The 4 Ways AI Can Help Boost Your Workplace Retention Efforts

Employee turnover is one of the costliest problems facing businesses today – but there are ways to leverage artificial intelligence to boost workplace retention. AI – especially Generative AI – offers promising solutions that go beyond mere automation. This Insight explores the transformative role of AI in four specific ways and gives you actionable steps you can use to enhance workplace loyalty and reduce turnover. We’ll discuss this issue and other AI developments at AI IMPACT – an FP Conference for Business Leaders this June 26-28 in Washington, D.C. Learn more and register here.

1. Recruiting and Onboarding

The work to retain employees begins before you even hire them. You are more likely to ensure you have invested and loyal workers if you select those that are best suited for the job. Some 83% of employers, including 99% of Fortune 500 companies, already use some form of automated tool as a part of their hiring process. So how can AI take this automation to the next level and help you select the candidates most likely to stick? By introducing “smart” automated processes that learn as they grow and more closely replicate human behavior. Some specific ways AI can aid your efforts:

• Job description creation. It takes time to write job descriptions that get the attention of candidates (not to mention adhering to the patchwork of salary disclosures and other legal requirements). Generative AI products can assist with the development of engaging job descriptions – at least solid first drafts – that will ensure you get the cream of the crop in your candidate pool.  
• Talent pool expansion. AI can also broaden your talent pool by identifying potential candidates who may not have applied to the job or who didn’t use the “right” keywords in their resumes but have the requisite skills and qualifications – and even make first contact with hidden gems.
• Resume review. Rather than wasting time culling through hundreds of resumes, AI can help you quickly source the best candidates.
• Bias elimination. When used correctly, Generative AI can also reduce instances of bias. For example, assisting in identifying the sorts of masculine-leaning terms in a job description that may dissuade women from applying (such as “driven” or “assertive”).  
• Prediction analysis. AI can also use predictive analytics to analyze candidate data, resumes, social media, online behavior, and other data sources to predict which candidates are most likely to be successful in the role.

You only have one chance to make a good first impression – so you should use AI to enhance the onboarding experience. A variety of tools are available to ease the process of bringing new employees aboard – whether being hired individually or as part of a larger scale orientation. For example, you can deploy AI-powered chatbots or other platforms to assist new employees as they navigate their first days and weeks at your organization and engage in necessary training exercises.

2. Employee Engagement

Now that you have hired top talent, you need an employee engagement strategy to keep them around. AI tools offer a sophisticated means to analyze countless potential data points related to employee activities and sentiments – which can be leveraged to effectively boost engagement.

• Data collection. These tools collect data from various sources such as employee output, emails, and digital communications. For instance, AI-driven analytics platforms can monitor trends in communication patterns, frequency of collaboration, and other indicators of engagement. By analyzing this data, AI can help identify areas where engagement is lacking and suggest targeted interventions.
• Employee interaction. AI can also actively interact with employees to gauge their satisfaction and well-being through automated chats or surveys conducted at regular intervals. This continuous feedback mechanism allows you to keep a pulse on the workforce’s mood without waiting for annual reviews. For example, AI-powered chatbots can initiate check-ins with employees, offering a platform for them to express concerns or provide feedback in a less formal, more immediate manner. This not only helps in addressing issues promptly but also fosters a culture of openness and continuous improvement.
• Spotting problems. Moreover, AI systems can be programmed to recognize signs of disengagement or burnout. They can alert managers and start the process of rolling out proactive measures. And they can even help tailor these measures and develop personalized retention strategies – such as career path discussions, role adjustments, or mentorship opportunities.

3. Learning and Development

AI’s role in learning and development is already revolutionizing how companies approach growth and training within their workforce.

• Personal customization. You can use AI to create personalized learning experiences tailored to the unique needs and career aspirations of each employee. These systems can analyze performance data, learning pace, and preferred learning styles to develop these programs. This personalized approach not only makes learning more effective but also increases employee satisfaction and loyalty.
• Furthermore, AI can facilitate the continuous development process by identifying skills gaps and recommending specific courses or learning modules to bridge these gaps. For example, AI algorithms can suggest that an employee who frequently works with data but struggles with certain analyses might benefit from a targeted statistics or machine learning course.
• Managerial feedback. Additionally, AI tools can assist HR managers and team leads in monitoring the progress of learning initiatives and evaluating their impact on performance. By providing real-time insights into how effectively training programs are being absorbed and applied, AI helps ensure that the time and resources invested in L&D yield tangible results.

4. Predictive Analytics

Predictive analytics is the foundation of AI. Indeed, the entire field is perfectly suited for AI – and for retention strategies.

• Identifying departing employees. By reviewing work patterns, supervisor feedback, historical data, and a whole host of other available information, some tools can offer your organization insights into which employees are at risk of disengagement or likely to leave. These tools assess a variety of factors, including job satisfaction scores, frequency of role changes, absence rates, and even subtle signals like changes in work habits or communication patterns. You can use that information to either double down on your retention efforts and see what you can do to improve their situation, or to help you make decisions about whether it is time to move on from that employee.
• Improving performance and teamwork. Predictive analytics extends far beyond identifying potential departures. It can forecast team performance and compatibility to help you guide decision-making in team assignments and project management. This preemptive approach not only helps in retaining talent but also improves productivity and job satisfaction across the board. For example, AI could suggest realigning team members based on complementary skills and communication styles, thereby fostering a more harmonious and effective work environment.
• Performing simulations. Finally, AI-driven analytics give you the ability to simulate potential changes to your organization and predict their impacts on employee retention. Your leaders can use scenario analysis tools to foresee the outcomes of various workplace policies, leadership changes, or even market conditions. This allows you to improve your strategic planning and your policies, giving you a more stable organization.

A Word About Ethics and Transparency

While there is a lot to gain from using AI-powered tools in the employee retention arena, you should review these tools with a critical eye. Danger can lurk in many possible areas at the intersection of AI and human capital management. 

• AI tools can be a helpful resource for employers, but they are not infallible. AI-powered systems are built by humans and use a system of judgment that generally reflects human characteristics. For AI that is “trained” on existing datasets in order to predict outcomes or generate content (like ChatGPT), those datasets necessarily reflect past human decision-making. For example, if you are seeking to hire individuals who reflect the characteristics of your already-successful employees and is trained using those employees’ data, the existing demographics of your company may impact results provided by an AI-analytics tool. 
• Similarly, some of these tools may fall prey to known shortcomings in the technology that can result in disparate impacts on employees in certain racial categories, women, older workers, or other diverse groups.

Many advocates on the forefront of the AI revolution preach the benefits – and the ethics – of transparency when it comes to your use of this technology during the hiring and management process. You may want to consider being fully upfront with candidates and employees about the way you deploy AI.

Moreover, such disclosures may soon be required under the law. New York and California lawmakers are currently debating bills that would mandate employers provide this high level of transparency through required notices – and a bipartisan federal proposal from Congress would do the same across the country. In fact, all these measures would also force employers to refrain from the use of AI in circumstances where the applicants or employees raise an objection. So it’s best not to turn over all of your retention efforts to robots but retain a healthy dose of human judgment in the mix.

Do You Want to Learn More?

If you are interested in learning more, sign up for AI IMPACT – an FP Conference for Business Leaders this June 26-28 in Washington, D.C. Learn more and register here.

Conclusion

We will continue to monitor these developments and provide the most up-to-date information directly to your inbox, so make sure you are subscribed to Fisher Phillips’ Insight System. If you have questions, contact your Fisher Phillips attorney, the authors of this Insight, or any attorney in our AI, Data, and Analytics Practice Group.