AI Agents for HR: 12 Use Cases

AI agents are software programs that can be assigned tasks, observe their environment, take actions based on their roles, and optimize their behavior based on their experiences and user feedback. They’re designed to help organizations automate and streamline tasks and improve decision-making. AI agents not only help provide guidance, but unlike predictive AI tools, they can also take action on behalf of the user, either when requested or on their own initiative, based on large language model (LLM) learning.

HR organizations are applying AI in a number of ways, including to quickly produce detailed job postings, give employees quick answers to routine questions about benefits and other topics, and create performance review summaries. But AI agents can support a deeper level of analysis and action. Working together seamlessly, AI agents can accept a request or directive, assign responsibility for different tasks to specialized agents (such as benefits, perks, onboarding, and rewards assistants), and use human language to provide users with the information they seek or let them know that a task has been performed. Although AI agents can be designed to work autonomously, humans help them become more effective by assessing their suggestions, providing feedback on the quality of their output, and even overruling recommended actions.

What Is an AI Agent?

AI agents are artificial intelligence-powered software tools that use generative AI and natural language interfaces to assist users with a variety of tasks, such as updating information in their employee record, updating benefits handbooks, and delivering a text summary of a complex table or chart. They use LLMs, which are machine learning models that can support natural language processing tasks, and retrieval-augmented generation (RAG), which provides a way to optimize the output of an LLM without modifying the model itself.

What Is an AI Agent in HR?

AI agents in HR can apply humanlike characteristics and capabilities such as reasoning, memory, and decision-making to common HR responsibilities, including recruiting, onboarding, benefits management, and talent management. AI agents embedded into HR workflows can access employee data in HCM systems, corporate documentation, finance data in ERP systems, and data from other internal sources, as well as data from external sources, such as industry compensation data and corporate benefits trends.

Agents can be sorted into two categories: conversational agents, which interact with humans or with other software programs, and functional agents, which are associated with a specific set of tasks or a specific role. For example, a performance management agent could be responsible for summarizing employee performance data, highlighting achievements or areas for improvement, and drafting personalized career development plans. A conversational agent could then communicate these potential career plans and take in and use feedback from the employee.

A hiring agent’s tasks could include documenting job requirements, reviewing GenAI-created job postings, and scheduling candidate interviews. A chatbot agent can communicate with job candidates, receive and analyze their feedback, and alert hiring managers when the next step requires human input. A benefits administrator agent can provide human language responses to employees who have questions about insurance coverage or other company benefits.

When employees ask questions, the conversational agent passes the request to the supervisory agent, which creates the plan and determines what actions are necessary to respond to the request. The supervisory agent may look to a GenAI agent to create the response. When specific knowledge regarding the company’s benefits offerings needs to be gathered, the supervisory agent calls on a RAG agent to fetch the appropriate data from the LLM and the company’s documentation repository. It also may direct an HR benefits analyst agent to retrieve information on an employee’s coverage options. Finally, the supervisory agent checks the final response from the LLM for accuracy before forwarding it to the conversational agent for communication with the employee.

The AI agent’s overarching goal is to help HR and line-of-business managers spend more time advising and building relationships with employees and less time on administrative tasks. Companies with engaged employees have 50% less employee turnover than those that don’t, according to a survey from the EY-Qualtrics Alliance.

Key Components of AI Agents in HR

Each AI agent receives inputs that feed its cognitive center, which in turn directs some kind of action. This could be an immediate action on behalf of the user or instructions to another agent to perform a specific task. Here are the three main components of the AI agent process as applied to HR functions.

• Input. AI agents can access structured data, such as salary ranges and employee demographics, and unstructured data, such as employee performance reviews and social media posts. They can use that data to define the parameters of a request. For example, a hiring manager agent might document a basic set of requirements for a particular job and then review a GenAI-created job posting for accuracy.
• Brain. An agent’s “brain” is responsible for making decisions or determining the next steps in a process based on the queries that were input and the repository of information generated by its LLM. Some agents may be responsible for determining the overall set of actions that need to take place; others may be responsible only for a single step.
• Action. Once the agent has evaluated the request, it takes action or directs another agent to take action. Tasks may include alerting a compensation agent that a request has come in for salary band information or salary history, verbalizing a response to a query, or updating company policies and distributing them to employees who might be affected by a change.

Key Benefits of AI Agents in HR

AI agents perform tasks on their own, combining GenAI capabilities with decision-making algorithms to help individuals and organizations set goals, develop action plans, complete tasks, and learn from feedback. Agents can converse with humans using their spoken language and are designed to handle complex problems and multistep processes that require knowledge of context and priorities. The following are key benefits.

• Increased efficiency and productivity. AI agents can help boost efficiency and productivity for HR staff and other employees by automating administrative tasks and the delivery of personalized career support, as well as by streamlining processes such as onboarding, employment contract development, performance reviews, and rewards and perks programs.
• Improved decision-making. AI agents can provide guidance to HR managers and other employees on topics such as industry compensation trends, retirement planning, and benefits coverage. Since AI agents handle multiple employee interactions, they can support decision-making within the HR organization by providing HR professionals with up-to-date, accurate information about workforce trends and sentiment.
• Reduced operational costs. AI agents can help HR organizations identify the best channels to use to promote job descriptions and communicate with job candidates, and they can help employees resolve issues they have with benefits, training, or scheduling. By taking on these tasks, they can save HR team members significant amounts of time.
• Enhanced employee experience. AI agents can help improve the overall employee experience by quickly providing employees with accurate answers to questions about benefits, salary, and other HR topics.
• Automated tasks. AI agents expand on predictive AI software capabilities by breaking down complex requests and solving them, allowing HR teams and managers to focus on strategic initiatives requiring human insight. While predictive AI tools can help solve simple tasks and well-defined problems, they’re not designed to act independently. AI agents can be assigned complex tasks, take actions based on their specific role, and use human feedback to refine future actions.

Top Use Cases for AI Agents in HR

The most common use cases for AI agents in HR take advantage of AI’s ability to analyze vast amounts of data to reduce administrative overhead and simplify mundane HR tasks. The following are some of the areas where HR professionals can expect to see benefits.

Career and Performance Development

AI agents can alleviate the burden of one of the most tedious HR tasks: writing performance reviews. Managers can instruct an agent to gather feedback from other team members, create a rough draft for their review, and even set up one-on-one time with the employee for a conversation. The AI agent handles the rote tasks, letting the manager and employee focus on a deeper conversation about job expectations and growth opportunities. AI agents can also recommend career goals based on an individual’s employment profile and interests, and they can help identify the steps the employee can take to achieve those goals. Employees can adjust those recommendations to help the AI agent learn.

• Career planning guide. TAI agents can capture notes from manager-employee career conversations, summarize the key points, help develop objectives as part of a career roadmap for the employee, and, if both parties approve the summary, add it to the employee’s record.
• Performance and goals assistant. Using the agent’s GenAI capabilities, a performance and goals assistant can help employees document their goals prior to performance reviews.
• Learning and training advisor. Employees can direct this AI agent to identify and sign them up for training programs that align with their career plans and current skill set. The advisor can also gather employee feedback on specific training modules and provide it to the appropriate HR staff.

Compensation and Benefits Management

Compensation and benefits management are two of the most valuable AI agent use cases. AI agents can provide employees with quick answers to questions about their salary and benefits while also helping support time tracking, and absence management.

• Timecard assistant. This AI agent can support the timely and accurate tracking of employee hours worked. Timecard assistants can also provide employees with context for how pay is calculated—for example, by clarifying overtime and incremental payment parameters.
• Tax withholding guide. An AI agent can help employees understand and elect their tax withholdings based on factors such as their number of dependents, disposable income level, and regular spending requirements.
• Compensation guidelines analyst. HR organizations can tap this type of AI agent to gather internal employee compensation data and industry trend data to provide guidance on compensation for new hires and existing employees. For example, an HR manager charged with reporting on industry salary trends can send an agent out to third-party sources to compile data, then use its GenAI capabilities to organize and summarize that data for a report to management.
• Leave and absence analyst. Employees can ask these AI agents questions about vacation time, sick days, and personal days, as well as family, medical, and other kinds of leave, and request additional information when necessary. They can even get preliminary approval for review by managers and HR.

Employee Lifecycle Management

Individuals and organizations can tap AI agents to help employees manage the progression of their careers. That includes both handling mundane tasks, such as updating employee records and helping employees explore educational offerings, and providing career guidance. AI agents can automate the mundane parts to free up managers for higher-level discussions.

• New hire onboarding assistant. This AI agent can help support employees during their first days and weeks on the job, letting them easily access information on company policies and alerting them about actions they must perform and required deadlines.
• Job seeker analyst. This type of AI agent can help employees explore career opportunities elsewhere in the organization by showing them open positions and the required skills. It can also provide resume tips and interview coaching.
• Perks and awards analyst. This AI analyst can keep employees informed about available perks and awards, such as those tied to length of service, performance, title, and other factors. For example, the agent may alert an employee that she’s entitled to fly business class now that she’s a VP or that she’ll receive a $5,000 bonus in her next paycheck on her 10-year work anniversary. It can also give managers guidance on related company policies.
• Personal and employment details assistant. This AI agent can help employees update their personal profiles in the company directory and access information on work milestones, such as promotion and transfer dates.
• Employee contracts analyst. This kind of AI agent can help employees understand the terms and conditions of their employment contracts by answering questions and summarizing the contents in easy-to-understand language. It can also track contractual requirements and deadlines so both employees and managers are aware of actions they must take, such as triggering the payment of bonuses or making plans to meet certification deadlines.

HR AI Agent Integrations

AI agents for HR rely on access to the comprehensive pay, performance, training, goals, and other data in an organization’s human capital management system. Connecting HR agents with those tied to the corporate ERP and other systems is just as crucial—for example, to give managers a high-level view of payroll across the organization to help with workforce planning and talent management. Interconnected systems can also be more secure, to the extent that sensitive HR, finance, sales, and other data is secured at the platform level and only authorized people can access it.

Transform Enterprise HR with AI Agents from Oracle

Oracle continues to build AI agent capabilities—for recruiting, hiring, career planning, performance management, and a host of other HR functions—into its Oracle Fusion Cloud HCM applications. The architecture is designed to make it easier for customers of its HCM and other Fusion Applications to extend their existing agents and create new agents, then deploy and manage them across the enterprise.

AI Agents in HR FAQs

How do AI agents improve recruitment in HR?

AI agents can help improve employee recruitment by creating job postings based on position requirements, identifying the applicants most aligned with the employer’s needs, and providing hiring managers with insights and recommendations to streamline the process. Agents can also help improve the experience of job candidates by answering their questions and guiding them through the application process.

What role do AI agents play in employee training and development?

AI agents can play an important role in employee training and development by making personalized recommendations to employees and using employee and manager feedback to refine that guidance.

How can AI agents manage performance reviews?

AI agents can help with performance reviews by recommending goals based on each employee’s skills, interests, and career plans and helping define success criteria. Managers can also ask the agent for advice on how to conduct better performance and goal discussions with employees.