Oracle expands the use of agentic artificial intelligence within its enterprise applications with new Fusion Agentic Applications and specialized AI agents in Human Resources. The company aims for AI to move beyond just answering questions or generating content and to proactively participate in processes such as training, internal mobility, job definition, and capacity planning.
The new features are integrated directly into Oracle Fusion Cloud Human Capital Management (HCM) and operate on Oracle Cloud Infrastructure (OCI). This approach is particularly interesting because agents can work with the corporate context available in Fusion: data, processes, internal policies, permissions, approval hierarchies, and operations.
Key points in 30 seconds
- Oracle introduces new agentic applications and AI agents into Fusion Cloud HCM.
- The agents are specialized for different HR tasks.
- They can collaborate to achieve objectives, rather than just answering questions.
- Oracle integrates them with Fusion data, workflows, permissions, and policies.
- Agents are available for designing jobs and keeping professional profiles up to date.
- AI can infer capabilities based on existing data in enterprise systems.
- There are also agents for creating training, recommending courses, and assisting team managers.
- Other agents analyze skill supply and demand within the organization.
- Oracle aims to shift from reactive talent management to continuous workforce planning.
- AI Agent Studio also allows creating and connecting custom agents, as well as those from Oracle, partners, and external sources.
Oracle wants AI to act within Human Resources
The main difference between these tools and the early generative AI assistants introduced in enterprise applications is primarily in their ability to act.
A traditional chatbot waits for a question. An agent can receive a goal, analyze information, reason about it, and participate in the necessary actions to achieve it.
Oracle describes its new Fusion Agentic Applications as systems composed of coordinated teams of specialized agents, result-oriented and prepared to execute business processes.
This enables more complex scenarios.
For example, an organization could detect that it will need certain professional capabilities over the next few months, identify employees who already possess some of these skills, and guide their training plans to internally cover these future needs.
The goal is to connect areas that traditionally operate relatively independently: jobs, skills, training, professional development, mobility, and workforce planning.
Agents that keep job definitions up to date
One of the initial blocks relates to what Oracle calls Work Architecture.
The new Job Architect Agent helps HR departments define and update jobs.
In many organizations, job descriptions remain almost unchanged for years, even as responsibilities and technologies evolve.
AI can help accelerate this process and ensure job models are aligned with current organizational priorities.
Along with this agent, there is Role Guide Generation Agent, responsible for helping generate documentation related to various roles.
Oracle aims to reduce manual work needed to prepare requirements and documentation before hiring or internal mobility processes.
AI can infer employees’ skills
Even more interesting is Intelligent Talent Profiles Agent.
The idea is to prevent internal professional profiles from relying solely on manually entered information by employees or HR.
People’s knowledge and skills evolve continuously.
An employee might participate in new projects, use new technologies, complete training, or take on different responsibilities without all that information being reflected in their corporate profile.
Oracle proposes using AI to infer skills based on available data in connected work systems.
This would allow keeping talent profiles more up-to-date and later using them for internal mobility, workforce planning, or professional development recommendations.
AI will also create training courses
Another area where Oracle introduces agentic automation is training.
Autonomous Content Authoring is designed to accelerate the generation of educational materials within companies.
The goal is to shift from processes where managers manually prepare much of the content to a system where AI can participate directly in content creation.
Oracle also introduces Agentic Courses, aimed at creating personalized and adaptive learning experiences.
Instead of offering the same curriculum to all employees, training could adapt based on individual profiles, skills, and needs.
Assigning training using natural language
Course management also gets its own agentic system.
Skills and Learning Assignment Management enables the use of natural language instructions to define audiences, assign training, and track compliance obligations.
This can be especially useful in large organizations.
Instead of manually setting numerous rules to determine who should complete certain training, managers can express conditions in natural language and let the system handle parts of the process.
Oracle also highlights its application to compliance training, where monitoring who must complete specific courses and verifying compliance can entail significant administrative effort.
A copilot for managers to better oversee their teams
Oracle also aims to bring these systems directly to managers.
The new Manager Coaching Workspace uses available context to provide recommendations related to employees’ professional development.
The goal is for conversations between managers and employees to be less dependent on the manager’s perception alone.
AI can provide contextual insights to help identify skills, improvement opportunities, or potential next steps in careers.
Also, Learning Representative for Managers Agent is a specialized agent for training support.
It can help answer questions about assigned courses and recommend specific learning activities.
Grow Coach: an agent to develop career paths
Employees will also have access to specialized agents.
Grow Coach aims to serve as a kind of career counselor within the company.
The agent can help prioritize development opportunities with the greatest impact and turn various training activities into a structured plan toward specific career goals.
This concept is closely related to internal mobility.
A company could identify positions it needs to fill and simultaneously assist employees in acquiring the skills required for those roles.
Enterprise Tutor automates part of manual searches
Oracle also introduces Enterprise Tutor Agent.
Its role is to help employees find relevant training within the organization’s catalog.
Instead of browsing through portals, applying filters, and manually reviewing numerous courses, a worker can directly specify what they want to learn.
The agent can answer questions and recommend related content based on needs.
This exemplifies the shift IA agents are bringing to enterprise applications: moving the interface from menus and searches to goal-oriented conversations.
Oracle aims to anticipate skill gaps in organizations
One of the most intriguing new capabilities relates to workforce planning.
Workforce Skills Supply vs. Demand Agent compares the supply and demand of skills within the organization.
Its purpose is to answer key HR questions:
What skills currently exist?
What capabilities will be needed?
Where are skills lacking?
Is hiring necessary or can internal talent be developed?
Oracle seeks to make this analysis more continuous and less reactive.
Understanding which professionals could fill future roles
Another agent, Careers-of-Interest Skills Supply vs. Demand Agent, extends this analysis to career mobility.
This tool can help explore current skills versus those needed for specific career paths or strategic roles.
It allows organizations to proactively identify employees who are relatively close to qualifying for future roles.
Instead of automatically turning to the labor market for vacancies, companies can develop a prepared internal talent pool for future openings.
Identifying where training investment is lacking
The third agent related to workforce planning is Development Resource Cold-Spot Analysis Agent.
Its job is to locate areas where resources allocated to professional development are insufficient compared to organizational priorities.
The idea is to avoid a one-size-fits-all approach to training investment.
AI can help direct resources toward departments, roles, or skills where they can have the greatest impact on the business.
From generative AI to process-executing AI
Oracle’s announcement reflects a broader shift in enterprise software.
Early generative AI focused on assistants capable of drafting emails, summarizing documents, or answering questions.
The next frontier is connecting models with real business processes.
This requires more than large language models; agents need to understand who the user is, their permissions, what data they can access, policies they must follow, and actions that require approval.
Oracle has an advantage here: Fusion already contains much of this enterprise context.
The new agentic applications can securely access unified data, workflows, policies, approval hierarchies, permissions, and transactional context.
AI Agent Studio enables building custom agents
Oracle’s strategy also extends beyond pre-built agents.
Fusion Applications customers have access to AI Agent Studio, a platform designed to build, connect, and run automation and agentic applications.
This platform supports agents that can be reused and developed by Oracle, partners, or third parties.
It points toward a future where enterprise applications operate through multiple specialized agents collaborating with each other and with employees.
Human Resources as a key domain for agentic AI
Applying autonomous agents in HR is particularly compelling because many decisions depend on data distributed across various systems.
Training, experience, open positions, organizational goals, skills, and workforce planning are often analyzed separately.
Oracle’s goal is to use AI to connect these insights seamlessly.
The ultimate aim is not just automating administrative tasks but creating a “talent agility” strategy: a company that continuously detects changing needs and adapts employee skills proactively before problems arise.
If successful, this approach could significantly transform HR operations.
AI in HR would go beyond simple chatbots that answer questions like “How many vacation days do I have?”
It would become an intelligent layer observing how roles, personnel, and organizational needs evolve, proposing decisions, and coordinating actions to prepare the workforce for the future.
