Generative AI is no longer a future vision – it is part of today’s HCM systems. Learn how SAP, Workday, Oracle, and UKG are embedding generative AI capabilities and what that means for your HR organization.
Generative AI refers to AI models that can independently create new content - such as text, code,or images. In HCM systems, such models are used for conversational assistants, generative text components, and data-driven recommendations.
Leading HCM vendors have by now integrated generative AI capabilities deeply into their systems. This article shows how SAP SuccessFactors, Workday, Oracle, and UKG are using this technology in practice.
SAP SUCCESSFACTORS
SAP integrates generative AI into SuccessFactors via SAP Business AI and the digital assistant Joule. Joule is a role-based copilot that identifies the user’s role based on existing role and authorization concepts and delivers tailored answers. Embedded directly into SuccessFactors screens, it enables employees, managers, and HR teams to interact in natural language.
Key Generative AI Features in SAP SuccessFactors
Joule as a Conversational Interface
- Joule understands the user role, context, and access rights, ensuring that only data the user is authorized to see is displayed.
- Supported interaction types: Informational (answering questions), Analytical (data analysis), Navigational (suggesting and opening Fiori apps), and Transactional (editing business objects directly).
- Available in many SuccessFactors modules, but requires premium AI licensing.
Specialized Joule Agents
In addition to Joule’s general assistant capabilities, SAP uses specialized AI agents in SuccessFactors to support specific HR processes. These agents are tailored to clearly defined use cases and operate within defined functional and organizational boundaries.
- In the Performance & Goals area, a dedicated agent supports managers in defining goals and drafting performance feedback. It serves as a structured starting point for performance conversations and development measures - final evaluation and decisions remain with the manager.
- For succession planning, specialized agents are planned that suggest successor options and document succession plans. These capabilities are being rolled out step by step. They support HR teams in identifying talent systematically and making succession processes more transparent.
- Another planned use case is the Case Handling Agent, which supports HR service teams in handling requests. It helps structure issues, consolidate relevant information, and escalate complex or critical cases
- Specialized agents are also planned for payroll-related scenarios. They are intended to support employees with payslip questions, detect anomalies, and explain deviations - without taking responsibility for payroll execution or approvals.
- In addition, the People Intelligence Agent provides analytical support. Connected to SAP Business Data Cloud, it delivers prepared workforce analytics and recommendations in natural language for HR practitioners. This makes complex data easier to access and interpret faster.
Security and Governance
SAP follows a “responsible by design” approach for Joule and Business AI:
- Role-based access: Joule only accesses data that users are authorized to see - even when explicitly prompted otherwise.
- Data protection & data ownership: Customer data remains under the organization’s control and is not used to train foundation models.
- Human-in-the-loop: AI supports sensitive talent decisions, but final review and approval always remain with people.
WORKDAY
Workday embeds AI, including generative AI, deep into the core of its HCM platform. A key element is the Workday Skills Cloud, which analyzes and normalizes skills from various data sources and makes them usable for recruiting, career planning, and learning.
Key Generative AI Features in Workday
Workday Skills Cloud with Generative Capabilities
- Analyzes skills from different sources, e.g., job descriptions, performance reviews, learning content, and external reference databases.
- Derives relevant skill suggestions for employees based on role, activities, and potential development paths.
- Supports personalized learning recommendations and career paths to promote internal mobility and targeted development.
Generative AI–Supported Self-Services and Assistance
- A conversational assistant enables interaction with the HCM system in natural language.
- e.g., checking vacation balances
- showing suitable internal roles based on existing skills
- navigating HR processes without manual search
- Personalized dashboards and automatically generated summaries provide relevant information for employees and managers.
Governance and Data Quality
Workday places particular emphasis on controlled and responsible use of generative AI:
- The Skills Cloud is based on normalized and validated data models to reduce bias and inconsistent outcomes.
- Human-in-the-loop applies to critical talent decisions such as promotions or placements.
- Transparent documentation of all AI-supported recommendations ensures traceability and auditability.
UKG (Ultimate Kronos Group)
UKG integrates generative AI via Google Cloud and Vertex AI into its workforce management and HCM solutions. The focus is on conversational interactions and data-driven insights for leaders.
Key Generative AI Features in UKG
Conversational HR Self-Services
- Employees can use natural language to request shifts, submit absences, clarify HR policies, or retrieve information.
- The conversational assistant understands context and can handle more complex requests.
- Direct integration into workforce management processes enables interactive shift management, for example.
Leader Recommendations and Insights
- AI-supported analytics show leaders how decisions affect engagement, retention, and productivity.
- The Bryte AI platform provides predictive insights into engagement risks, turnover probability, and optimization opportunities.
Security and Ethics
UKG positions secure and responsible AI as a core principle:
- Clear requirements for data protection, access controls, and encryption.
- A focus on fairness and bias controls to avoid discrimination in workforce decisions.
- Traceable compliance documentation for all AI-supported recommendations.
ORACLE
Oracle has systematically integrated generative AI into Oracle Fusion Cloud HCM and provides these capabilities via Oracle Cloud Infrastructure (OCI) Generative AI services. The approach is based on a variety of predefined, semi-autonomous AI agents that support clearly scoped tasks within defined workflows.
Key Generative AI Features in Oracle
Predefined AI Agents and Use Cases
- Recruiting: Job Discovery Agent (matching candidates to internal roles), Interview Management Agent (interview scheduling), Job Description Agent
- Performance & Compensation: Performance Analytics Agent, AI-supported feedback generation, compensation analysis
- Learning & Development: Learning Tutor Agent with course recommendations and personalized learning paths
- Payroll: Payroll Run Analyst for detecting deviations and a Pay Explanation Assistant
- Talent Management: Succession Planning Agent and Team Goals Assistant to support goal setting and succession planning
- HR Services: Onboarding Assistant, Timecards Assistant, Scheduling Assistant
AI Agent Studio
- Enables organizations to configure and adapt their own AI agents, e.g., based on internal policies, processes, or terminology.
Analytics AI Assistant
- Querying and analyzing HR and business data in natural language
- Automatic creation of reports and insights for relevant HR metrics
Data Governance and Security
Oracle places strong emphasis on data ownership and regulatory compliance:
- Customer data is not used to train foundation models.
- Strict tenant isolation: Data remains logically separated and is used only for the specific function.
- Compliance with data protection and regulatory requirements.
- Human-in-the-loop: AI supports sensitive talent decisions, but final review and approval always remain with people.
Market Reactions and Governance
Generative AI is among the most discussed and widely adopted topics in HR. The initial question “Should we use genAI in HCM?” has largely been answered: large enterprises and many mid-sized organizations are rolling out these capabilities or actively piloting them.
The Focus Has Shifted
The discussion is no longer about “whether,” but about “how”: how do we use generative AI responsibly, transparently, and compliantly?
Typical Opportunities
Relief from routine work: drafting job postings, performance feedback, and first-level HR inquiries can be supported or automated, freeing HR capacity for more strategic work.
Personalized recommendations: employees receive tailored information on careers, learning, and skills development faster.
Better data analysis: large data volumes can be analyzed faster and patterns in engagement, turnover, and skill gaps can be identified.
Improved user experience: conversational interfaces make HCM systems more intuitive and accessible.
Typical Concerns and Risks
- Quality and trustworthiness: generated content can be incorrect, biased, or misleading if training data or context is insufficient.
- Bias and fairness: models can inherit and amplify discriminatory patterns from historical data - especially in recruiting, performance evaluation, or compensation.
- Overreliance and control: if HR teams lean too heavily on AI recommendations, human judgment can erode.
- Data quality and security: sensitive employee data must be protected; poorly structured or missing data leads to lower-quality outputs.
- Regulatory risk: the EU AI Act, local data protection laws, and internal compliance requirements set clear limits for AI use.
Governance as Best Practice
Leading organizations implement:
- AI policies and guidelines: clear rules for which AI capabilities are allowed in which processes.
- Human-in-the-loop controls: for critical HR decisions (hiring, promotion, termination), people remain the decision-makers; AI supports but does not decide.
- Training and change management: HR and manager teams are trained to use AI effectively and understand its limits.
- Audit and documentation: AI-supported recommendations and decisions are documented and traceable (auditable).
- New roles: AI stewards, data governance officers, trainers, and compliance specialists become increasingly important.
Outlook for HCM Users
Generative AI is no longer an experiment but a standard component of modern HCM systems. For organizations using SAP SuccessFactors, Workday, Oracle, or UKG, the question is less whether, and more how to use these capabilities responsibly and effectively.
What Can Organizations Do Now?
1. Start with a Step-by-Step Rollout
- Start with clearly scoped, low-risk use cases to gain experience:
- Creating job posting drafts (with subsequent manual review)
- Suggestions for performance feedback text as a starting point for managers
- Conversational HR self-services for policy and process questions
This creates fast learning effects at manageable risk.
2. Build Governance
- A structured framework is a prerequisite for sustainable use of generative AI:
- Define an AI policy that specifies which capabilities are permissible in which HR processes.
- Establish an AI governance board (HR, IT, data protection, compliance, works council).
- Ensure traceable documentation of all AI-supported decisions.
3. Training and Change Management
- Success depends on the people who use these capabilities:
- Targeted training for HR teams and leaders on using AI assistance features
- Building AI champions who act as multipliers in the organization
- Transparent communication to the workforce about where and why AI is used and its limits
4. Ensure Data Quality
- Generative AI is only as good as the underlying data:
- Ensure complete and up-to-date employee data
- Normalized and consistent data structures (e.g., skills, roles, qualifications)
- Regular bias and quality checks of the data foundation
5. Define Measurable KPIs
To make value measurable, define clear KPIs such as:
- Time saved per HR process
- Improvements in candidate experience
- Reduction of HR service requests
- Quality and acceptance of generated content
These KPIs help set priorities and continuously improve the initiative.
Conclusion
Generative AI is transforming HR - now is the right time to actively shape adoption.
If you use SAP SuccessFactors, Workday, Oracle, or UKG and want to introduce generative AI in your HR organization in a targeted, safe, and compliant way, we’re happy to support you.
binder|consulting supports you with:
- Assessments: Identifying potential in your existing HCM environment
- Roadmap development: Prioritizing use cases and establishing sustainable governance
- Implementation & Change: Supporting pilots, rollout, and enablement
- Governance & Compliance: Ensuring ethical and compliant AI use
Written by: Rico Schirrmeister
