With low unemployment and hybrid work continuing, HR leaders must continue to prioritize employee experience to help organizations retain top talent. Technologies such as hyperautomation and large language models help companies improve the employee experience.
Companies use hyperautomation to onboard new employees, use conversational AI to answer employee questions, use large-scale language models (LLM) to analyze employee satisfaction data, Create HR content.
Learn more about how this AI-powered technology can help improve the employee experience.
Hyper-automation for onboarding
Onboarding is an important part of the employee experience, as first impressions set the mood for new hires. From the moment the offer letter is signed, HR must work with the new employee to complete a myriad of tasks such as background checks, drug testing, requesting access to equipment and software, payroll setup, compliance training, and more. . Additionally, the process often involves disparate systems and external vendors, which can make the process more difficult to complete, and companies may have to delay the onboarding date for new hires.
Hyperautomation makes it easy for onboarding managers and recruiters to complete these tasks. Typically, onboarding managers ensure that new hires successfully complete one task before moving on to the next, but hyperautomation tracks the sequence of events and triggers subsequent ones to keep the process moving. can proceed more quickly. For example, once an employee background check is completed, the process immediately transitions to drug testing. With hyperautomation, HR staff no longer have to manually navigate the onboarding process and keep employees waiting.
Conversational AI for employee questions
New and veteran employees may struggle to find the benefits information they need, as benefits information can be scattered across company intranets, knowledge articles, and various HR systems. Additionally, employees may need to answer benefits questions outside of hours when the benefits team isn’t checking messages. For example, an employee might ask about his health insurance when he takes his child to the emergency room on Saturday afternoon.
If your company uses conversational AI, employees can instead ask the AI what benefits they want.
LLM for Employee Research Insights
LLM and generative AI use natural language processing and probability to understand and predict trends in data and answer questions in a consistent manner. For example, instead of an HR manager forwarding an email request and answering a question, an AI model would classify the email, use generative AI to answer some questions, and then route more complex questions to the appropriate HR manager. You can route to resources to speed up the response process.
Other potential LLM and generative AI use cases for HR include creating employee satisfaction surveys and exit interview data. Both provide valuable insight into company culture, allowing LLMs to identify patterns and generate sentiment analysis. This data helps HR managers create strategies that improve employee engagement and morale.
