Integration

AI Integration for UKG HR Service Delivery

Build AI-powered HR service agents and automate case management workflows on top of UKG HR Service Delivery. Reduce ticket volume, improve resolution times, and provide 24/7 employee support.

Get in touch Learn more

Developer designing multi-agent workflow on laptop, architecture diagram on screen, casual home office setup with afternoon light.

ARCHITECTURE AND ROLLOUT

Where AI Fits in UKG HR Service Delivery

A practical guide to integrating AI agents and automation into UKG HR Service Delivery for faster case resolution and proactive employee support.

AI integration for UKG HR Service Delivery focuses on three primary surfaces: the employee portal, the agent workspace, and the backend case management APIs. The goal is to intercept and resolve common inquiries before they become manual tickets, and to augment HR agents with context and suggested actions for complex cases. Key integration points include:

Employee Self-Service Portal: Embedding a conversational AI assistant to answer policy questions (e.g., PTO balance, benefits), guide form completion (e.g., address change), and initiate standard service requests using UKG's APIs.
Case Management Queue: Applying AI for intelligent ticket triage, automatically categorizing incoming cases (e.g., Payroll, Benefits, Onboarding), assigning priority, and routing to the correct team or pre-built workflow.
Knowledge Base & Resolution Actions: Connecting AI to the UKG knowledge repository to retrieve accurate answers for agents and, where permissions allow, enabling the AI to execute safe, predefined actions like updating a phone number or generating a verification letter via the UKG Service Delivery API.

A production implementation typically involves a middleware layer (an AI orchestration platform) that sits between the AI model and UKG. This layer handles authentication, API call formatting, prompt context management, and audit logging. For example, when an employee asks "How much vacation do I have?", the orchestration layer would:

Securely call the UKG API to retrieve the employee's accrual data.
Format this data into a natural-language response using a governed prompt template.
Log the query and response for compliance.
Optionally, trigger a follow-up workflow if the employee then asks to "submit a vacation request," creating a draft case in UKG with pre-filled details.

This architecture keeps the core HR system of record intact while adding an intelligent interaction layer. The impact is operational: deflecting 30-50% of tier-1 inquiries, reducing average handle time for agents by providing case summaries and next-best-action suggestions, and improving employee satisfaction through 24/7 instant support.

Rollout should be phased, starting with a low-risk, high-volume use case like answering FAQ from a curated knowledge base. Governance is critical: all AI-generated actions should require agent approval or be limited to low-risk transactions, with a full audit trail. Change management must train HR agents to work with the AI as a copilot, not view it as a replacement. For a deeper dive on building secure HR assistants, see our guide on AI Integration for HR Chatbots and Virtual Assistants. Success depends on tight integration with UKG's data model and a clear process for maintaining the AI's knowledge as policies evolve.

ARCHITECTURAL BLUEPRINTS

Key Integration Surfaces in UKG HR Service Delivery

Case Management & Knowledge

The UKG HR Service Delivery case management engine is the primary surface for AI integration. AI agents can be triggered by new case creation via webhook to perform initial triage, classification, and routing. This involves analyzing the unstructured text in the case description against a knowledge base of HR policies, FAQs, and past resolutions.

Key integration points include:

Case API: To retrieve case details, add internal notes with AI-generated summaries or next-step suggestions, and update case status or assignee.
Knowledge Management API: To ground AI responses in the official, approved UKG knowledge base, ensuring answers are consistent and compliant.
Webhooks: To subscribe to case creation, update, or closure events, triggering AI workflows in real-time.

A common pattern is an AI agent that reads a new case, suggests a resolution from the knowledge base, and either auto-resolves it (for simple queries) or routes it to the correct HR specialist with a detailed summary, reducing first-response time from hours to minutes.

PRACTICAL INTEGRATION PATTERNS

High-Value AI Use Cases for UKG HR Service Delivery

Integrating AI into UKG HR Service Delivery transforms the employee and HR team experience by automating case resolution, surfacing insights, and orchestrating complex workflows. These patterns connect directly to UKG's case management, knowledge, and employee data APIs.

AI-Powered HR Case Triage & Routing

An AI agent analyzes incoming case descriptions in UKG, classifies the issue (e.g., Payroll, Benefits, Leave), assigns priority, and routes it to the correct HR specialist queue. It can also suggest knowledge base articles for deflection, reducing manual sorting time.

Batch -> Real-time

Routing speed

Employee Self-Service Virtual Agent

Deploy a conversational AI assistant integrated with UKG's APIs to answer common policy questions, guide employees through self-service tasks (e.g., address changes, pay stub access), and even create cases on their behalf—all within your existing HR portal.

Hours -> Minutes

Resolution time

Automated Case Summarization & Resolution

For complex cases, an AI copilot summarizes lengthy email threads and case notes from UKG, drafts resolution responses for HR agent review, and suggests next steps based on policy. This cuts down on manual documentation and ensures consistency.

1 sprint

Typical implementation

Proactive Sentiment & Risk Detection

Continuously analyze case data, survey feedback (integrated via UKG Pro or external sources), and communication tone to detect emerging issues (e.g., department-wide morale drops). The AI can automatically create leadership alerts or proactive outreach campaigns in UKG.

Same day

Insight delivery

Intelligent Knowledge Base Curation

An AI agent monitors resolved cases in UKG HR Service Delivery to identify gaps in the official knowledge base. It can draft new FAQ entries from successful resolutions and suggest updates to outdated articles, keeping support content current and reducing repeat inquiries.

Multi-System Onboarding Orchestration

Trigger a complex onboarding workflow from a UKG hire event. An AI agent orchestrates tasks across IT (provisioning), facilities (badge access), and payroll systems, updating the UKG case with status and escalating any delays—moving from checklist management to intelligent coordination.

Days -> Hours

Process coordination

FOR UKG HR SERVICE DELIVERY

Example AI-Augmented Workflows

These workflows illustrate how AI agents can automate high-volume inquiries, guide complex processes, and proactively manage HR service delivery cases within UKG, reducing manual effort and improving employee experience.

Trigger: An employee submits a question via the UKG HR Service Delivery portal, email, or integrated chat (e.g., "How much PTO do I have left?" or "What is the bereavement leave policy?").

Context/Data Pulled: The AI agent authenticates via UKG's API, retrieves the employee's record, and accesses the centralized policy knowledge base.

Model or Agent Action:

Classifies the inquiry intent (e.g., leave_balance or policy_lookup).
For balance queries, calculates available entitlements based on accrual rules, used balances, and upcoming approved leave.
For policy questions, retrieves the relevant, approved policy text and any location-specific or employee-status nuances.

System Update or Next Step:

The agent generates a precise, personalized response and posts it as a comment on the case in UKG, marking it for auto-resolved status.
If the inquiry requires human action (e.g., a complex leave situation), the agent escalates the case to an HR specialist with a full context summary and suggested next steps.

Human Review Point: All auto-resolved cases are logged in an audit queue for weekly sampling by HR operations to ensure accuracy and refine the agent's knowledge.

PRODUCTION-READY INTEGRATION PATTERNS

Implementation Architecture: Data Flow & Guardrails

A secure, governed architecture for connecting AI agents to UKG HR Service Delivery data and workflows.

A production AI integration for UKG HR Service Delivery is built on a secure middleware layer that sits between your AI models and UKG's APIs. This layer handles authentication, data transformation, and audit logging. Core data flows include:

Query Resolution: An employee asks a question via chat. The AI agent uses a Retrieval-Augmented Generation (RAG) system to search a vector index of HR policies and knowledge articles, then calls UKG's Case Management API to retrieve the user's specific case history before formulating a response.
Workflow Execution: For actionable requests like "submit a leave request," the agent validates the request against UKG's Leave Accruals data, constructs the proper JSON payload, and posts it to the UKG Business Logic API to create a new case or transaction, returning the case ID to the user.
Data Synchronization: A background process periodically syncs relevant UKG data (e.g., employee profiles, policy documents, open cases) to a private vector database, ensuring the AI's knowledge remains current without live querying the production system for every request.

Governance is enforced at multiple levels to ensure security and compliance:

API Gateways & RBAC: All calls to UKG APIs are routed through an API gateway that enforces rate limits and applies role-based access control, ensuring the AI agent only accesses data scoped to the inquiring employee or its support role.
Prompt Guardrails & Logging: Every user prompt and AI response is logged with a session ID, user ID, and timestamp. A secondary classification model screens outgoing AI responses for policy violations or sensitive data leakage before delivery.
Human-in-the-Loop Escalation: The architecture defines clear escalation thresholds. If an AI agent's confidence score is low or the requested action requires approval (e.g., a sensitive data change), the workflow automatically creates a task in UKG HR Service Delivery for a human agent, maintaining the system of record.

Rollout follows a phased approach, starting with a pilot on low-risk, high-volume inquiry types (e.g., PTO balance, policy lookups) before expanding to transactional workflows. This allows for tuning the RAG retrieval, refining guardrails, and measuring deflection rates. The final architecture supports seamless integration with other pillars like /integrations/it-service-management-platforms for cross-functional employee issues and /integrations/enterprise-content-management-platforms for document-intensive processes, creating a unified employee service hub.

UKG HR SERVICE DELIVERY

Code & Payload Examples

Automating Incoming Case Classification

An AI agent can listen for new cases via UKG's webhook or API and instantly classify them, assign priority, and route them to the correct queue. This reduces manual triage and speeds up resolution.

Example Webhook Handler (Python):

python
import requests
from openai import OpenAI

client = OpenAI(api_key=YOUR_API_KEY)

def handle_ukg_case_webhook(case_data):
    """Process a new case from UKG HR Service Delivery."""
    # Extract the employee's question from the case
    case_subject = case_data.get('subject', '')
    case_description = case_data.get('description', '')
    case_id = case_data.get('caseId')
    
    # Use LLM to classify and route
    prompt = f"""Classify this HR inquiry for routing:
    Subject: {case_subject}\n\nDescription: {case_description}\n\nCategories: Benefits, Payroll, Time-Off, Policy, IT/Systems, Onboarding, Other.
    Return JSON with: category, priority (1-5, 1 highest), suggestedAssignmentGroup."""
    
    response = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": prompt}],
        response_format={ "type": "json_object" }
    )
    
    classification = json.loads(response.choices[0].message.content)
    
    # Update the case in UKG via API
    update_payload = {
        "caseId": case_id,
        "category": classification['category'],
        "priority": classification['priority'],
        "assignmentGroup": classification['suggestedAssignmentGroup']
    }
    
    # Call UKG API to update case (pseudocode)
    # ukg_api.patch(f'/cases/{case_id}', json=update_payload)
    
    return classification

This pattern uses the case's initial description to predict the correct team, ensuring faster first-touch resolution.

AI-Enhanced HR Service Delivery

Realistic Time Savings & Operational Impact

This table illustrates the operational impact of integrating AI agents and automation into UKG HR Service Delivery, focusing on measurable improvements in HR team efficiency and employee experience.

HR Service Workflow	Before AI Integration	After AI Integration	Implementation Notes
Employee Policy & Pay Inquiry Triage	Manual ticket review and routing (15-30 min avg.)	AI-powered instant classification & routing (<1 min)	Agent deflects or routes 70%+ of common inquiries; complex cases flagged for specialists.
Case Summarization & Context	Agent reads full case history (5-10 min per case)	AI generates one-paragraph summary with key data (<30 sec)	Summary includes employee record highlights, prior interactions, and pending items.
Benefits Enrollment Guidance	Scheduled 1:1 calls or lengthy email chains	Interactive AI guide with personalized recommendations	AI uses UKG data to model scenarios; final submission via UKG API with human review.
Onboarding Task Orchestration	Manual checklist management across IT, Facilities, Payroll	AI-driven multi-system workflow triggered from UKG hire event	AI monitors task completion across systems; alerts HRBP for exceptions.
Manager HR Support (e.g., comp changes)	HRBP researches policy, drafts communication, processes in UKG	AI copilot drafts compliant change rationale & prepares UKG transaction	Manager reviews and submits; audit trail maintained in UKG.
Compliance Audit Data Pulls	Manual report building and data validation (hours to days)	AI-generated audit reports with anomaly flags (same-day)	AI queries UKG APIs and DataHub; HR reviews flagged items before submission.
Knowledge Base Article Updates	Quarterly manual review by HR team	AI suggests updates based on ticket analysis & policy changes	HR approves AI suggestions; articles sync to UKG Knowledge Management.

ARCHITECTING FOR ENTERPRISE HR

Governance, Security, and Phased Rollout

A practical blueprint for deploying AI in UKG HR Service Delivery with control, security, and measurable impact.

Integrating AI into UKG HR Service Delivery requires a security-first architecture that respects the sensitivity of employee data. This means implementing a zero-trust API layer where AI agents act as a controlled intermediary. All queries to UKG Pro or UKG Ready APIs—whether fetching an employee's leave balance via the TimeOff object or updating a case status in the ServiceDelivery module—are routed through a governance service. This service enforces role-based access control (RBAC), logs all interactions for audit trails, and masks sensitive fields like Social Security Numbers before data is sent to the LLM for processing. The AI system should never store persistent UKG data, operating instead as a stateless query and action engine.

A successful rollout follows a phased, use-case-driven approach, not a big-bang deployment. Phase 1 typically starts with a read-only HR assistant deployed to a pilot group. This agent answers common policy questions by retrieving information from UKG knowledge articles and org data, deflecting Tier 1 tickets. Phase 2 introduces controlled write-backs, such as an agent that can submit a Case creation request for a hardware issue, which still routes through the existing UKG approval workflow. Phase 3 expands to multi-step orchestration, like guiding a manager through a promotion workflow by pulling compensation benchmarks, drafting documentation, and submitting the JobChange transaction—all with a human-in-the-loop approval step before any system-of-record update is finalized.

Governance is continuous, not a one-time setup. We recommend establishing a cross-functional AI steering committee with HR, IT, Legal, and Security to review new agent capabilities, monitor performance metrics (deflection rate, user satisfaction), and audit logs for anomalous activity. All AI-generated content, such as draft manager feedback or policy summaries, should be clearly labeled as AI-assisted. This phased, governed approach de-risks implementation, builds organizational trust, and ensures the AI integration delivers tangible operational relief—reducing HR case resolution time from hours to minutes—while keeping UKG as the single source of truth.

Enabling Efficiency, Speed & Accuracy

Intelligent Analysis, Decision & Execution

We build AI systems for teams that need search across company data, workflow automation across tools, or AI features inside products and internal software.

Talk to Us

Search across company data

Give teams answers from docs, tickets, runbooks, and product data with sources and permissions.

Useful when people spend too long searching or get different answers from different systems.

Enterprise searchRAGPermissions

Automate internal workflows

Use AI to route work, draft outputs, trigger actions, and keep approvals and logs in place.

Useful when repetitive work moves across multiple tools and teams.

AI agentsWorkflow automationGovernance

Add AI to products and internal tools

Build assistants, guided actions, or decision support into the software your team or customers already use.

Useful when AI needs to be part of the product, not a separate tool.

AI integrationDecision supportModel routing

AI INTEGRATION FOR UKG HR SERVICE DELIVERY

Frequently Asked Questions

Practical questions about implementing AI agents, automation, and copilots on the UKG HR Service Delivery platform.

Access is managed through UKG's API framework, typically using OAuth 2.0 for authentication. Implementation follows these key patterns:

Service Account with Scoped Permissions: The AI agent uses a dedicated service account with a narrowly defined role in UKG, granting access only to the specific objects and APIs needed (e.g., Case, Employee, KnowledgeArticle).
API Gateway & Policy Enforcement: All AI agent requests route through a secure API gateway. This layer enforces rate limiting, logs all queries for auditability, and can apply additional data masking or filtering rules before the request reaches UKG.
Contextual Data Retrieval: The agent's prompts are dynamically constructed to only request the data necessary for the task. For example, when answering a pay question, the system retrieves only the employee's pay statement for the relevant period, not their entire employment history.
Zero Data Persistence (Optional): For highly sensitive queries, the architecture can be configured so the LLM receives data for in-context processing only, with no intermediate storage in vector databases or logs.

This approach ensures the AI operates within the same security and permission model as any other integrated application.

About the author

Prasad Kumkar

CEO & MD, Inference Systems

Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.

His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.

Limited slotsGet a Free AI Consultation

How We Work

Custom AI workflows for your Business

One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.