Case study
How an HR Automation Solution Reduced Back-Office Effort by 80% for a Leading APAC Energy & Utilities Enterprise
- Team size: 10
- Development time: 6 months
Explore more case study
Background
Across large enterprises, HR teams spend a significant portion of their time answering repetitive employee questions about company policies, leave requests, onboarding, benefits, and personal records instead of focusing on strategic workforce initiatives. At the same time, employee expectations for instant, always-available support continue to rise as organizations expand across multiple regions and languages.
According to Gartner’s 2026 CHRO Priorities, AI-driven HR transformation has become one of the top strategic priorities for enterprise HR leaders, with evolving the HR operating model expected to deliver the highest AI productivity gains (29%). Meanwhile, Deloitte’s 2026 Global Human Capital Trends found that 7 in 10 business leaders now prioritize organizational speed and agility, increasing pressure on HR teams to modernize service delivery and employee support.
Our client, a leading energy and utilities enterprise operating across the Asia-Pacific region – was facing growing pressure to modernize its HR operations. Supporting thousands of employees working across power generation facilities, transmission networks, regional offices, and field operations, the HR team handled a high volume of repetitive enquiries related to onboarding, leave policies, employee benefits, mandatory compliance training, internal mobility, and personal HR records.
HR knowledge was distributed across employee handbooks, safety regulations, operational procedures, HR policies, knowledge bases, and multiple HR systems. As a result, HR specialists often spent considerable time searching, validating, and interpreting information before responding to employees. Maintaining consistent policy interpretation across different countries, business units, and languages became increasingly difficult as the workforce continued to expand.
Beyond improving employee experience, the organization also needed to ensure enterprise-grade governance over sensitive employee data while supporting multilingual self-service for a geographically distributed workforce. The client therefore engaged GEM to build an enterprise HR automation solution that could centralize HR knowledge, automate routine employee support, and establish a secure AI foundation capable of scaling with future HR transformation initiatives.
GEM designed and implemented a governed HR automation solution on the Databricks Data Intelligence Platform, transforming fragmented HR knowledge into an intelligent AI assistant capable of delivering personalized, multilingual employee support around the clock.
Challenges
Before implementation
Before implementing the HR automation solution, the client faced several operational and technology challenges that limited the efficiency and scalability of enterprise HR services.
- HR teams spent significant time answering repetitive enquiries related to leave policies, onboarding, employee benefits, compliance training, and internal HR procedures.
- HR knowledge was fragmented across HR systems, employee handbooks, operational procedures, safety documentation, and regional policy documents, making it difficult to provide consistent and up-to-date guidance.
- Employees working across power plants, field operations, and regional offices depended on HR staff for routine requests, creating delays outside normal business hours.
- As the workforce expanded across multiple countries, maintaining consistent policy interpretation and multilingual support became increasingly challenging.
- Scaling employee support required additional HR resources while maintaining governance and compliance over sensitive employee information.
During implementation
- The solution needed to support a geographically distributed workforce while delivering a consistent multilingual employee experience.
- AI responses had to be grounded exclusively in approved HR knowledge and the latest corporate policies.
- Sensitive HR requests required Human-in-the-Loop approval without disrupting employee self-service.
- Enterprise-grade governance, auditability, and security controls had to protect employee information throughout the AI lifecycle.
- The architecture needed to remain modular to support future HR capabilities and enterprise AI initiatives.
Solution
HR Automation Solution for Enterprise Self-Service and Intelligent HR Operations
Following an assessment of the client’s HR operating model, GEM designed and implemented an enterprise HR automation solution on the Databricks Data Intelligence Platform. The solution was built to support a geographically distributed workforce across power generation facilities, field operations, and regional offices by centralizing HR knowledge, automating routine employee support, and establishing a secure AI foundation for future HR transformation.
Centralized HR Knowledge for Consistent Answers
As the foundation of the HR automation solution, GEM consolidated employee handbooks, HR policies, safety and compliance documentation, onboarding materials, benefits information, and internal knowledge articles into a governed Lakehouse. By creating a single source of truth, employees received consistent, policy-grounded answers regardless of their location, language, or business unit, while HR teams only needed to maintain one centralized knowledge repository.
AI-Powered Employee Self-Service
GEM implemented a multilingual AI HR assistant capable of automatically handling common employee enquiries, including leave requests, onboarding guidance, employee benefits, compliance training requirements, and personal information lookup. Employees working from regional offices, operational sites, and field locations could access HR support 24/7 without waiting for HR business hours, significantly reducing repetitive administrative workload.
Real-Time Policy Retrieval with Governed RAG
To ensure the HR automation solution always delivered accurate responses, the solution leveraged Retrieval-Augmented Generation (RAG) with Databricks Vector Search. Whenever HR policies, compliance requirements, or employee documentation were updated, the AI assistant automatically retrieved the latest approved content without requiring model retraining, ensuring accurate and compliant guidance across the organization.
Automated HR Workflows with Multi-Agent AI
Rather than relying on a single chatbot, GEM implemented a multi-agent architecture where specialized AI agents independently handled policy enquiries, employee record retrieval, onboarding support, leave management, compliance training guidance, and workflow execution. Requests were intelligently routed to the most appropriate agent, improving response accuracy while enabling future expansion into additional HR services.
Enterprise Governance and Human Oversight
Because the client managed sensitive employee information across multiple countries, enterprise governance was embedded throughout the solution. Unity Catalog provided centralized data governance, role-based access control, lineage, and auditing, while Human-in-the-Loop workflows ensured sensitive HR decisions remained under human review. This enabled the organization to automate routine HR services without compromising security or regulatory compliance.
Continuous AI Quality Monitoring
To continuously optimize the HR automation solution after deployment, GEM integrated Mosaic AI Agent Evaluation, MLflow, and automated response monitoring to continuously measure answer quality, reasoning transparency, and user feedback. This enabled the client to improve AI performance over time while maintaining enterprise-grade governance and operational reliability.
Tech stack
- Data foundation: Delta Lake, Unity Catalog (governance, lineage, access control), Lakehouse ingestion and document parsing
- Retrieval: Databricks Vector Search (auto-synced with Delta Lake)
- Agents: Mosaic AI Agent Framework, Agent Bricks (incl. the Knowledge Assistant pattern)
- Models: Mosaic AI Model Serving, Foundation Model APIs, multi-provider catalog (Claude, Llama, Gemini, GPT), Mosaic AI Gateway
- Quality & ops: Mosaic AI Agent Evaluation (LLM-as-judge + human feedback), MLflow tracing
- Delivery: Databricks Apps (chat interface), governed tools and MCP for third-party actions
Output
The project successfully delivered a production-ready HR automation solution tailored to the client’s enterprise HR environment.
Key deliverables included:
- Built a multilingual AI HR assistant supporting employees across regional offices, operational sites, and field locations.
- Established a governed enterprise HR knowledge platform that unified HR policies, employee handbooks, compliance documentation, and operational procedures into a single source of truth.
- Implemented a production-ready Retrieval-Augmented Generation (RAG) architecture using Databricks Vector Search to ensure responses were always grounded in the latest approved HR information.
- Enabled secure AI-powered employee self-service for leave requests, onboarding, employee benefits, compliance training, and HR policy enquiries.
- Integrated the assistant with enterprise HR systems, employee records, and internal knowledge repositories.
- Established enterprise-grade AI governance through Unity Catalog, audit logging, AI guardrails, and Human-in-the-Loop workflows.
- Automated routine HR enquiries through specialized multi-agent orchestration while maintaining human oversight for sensitive actions.
- Delivered a scalable AI foundation capable of supporting future HR services and additional enterprise AI use cases.
Impacts
Operational efficiency
- Reduced HR back-office effort by more than 80% by automating high-volume employee enquiries related to leave, onboarding, benefits, HR policies, and personal records.
- Improved onboarding efficiency by over 80%, enabling new employees across regional offices and operational sites to access onboarding information through AI-powered self-service instead of manual HR support.
- Enabled 24/7 multilingual HR support for employees working across power generation facilities, field operations, and corporate offices, eliminating dependence on HR business hours.
- Delivered consistent policy interpretation by grounding every response in approved HR policies, employee handbooks, and compliance documentation, reducing inconsistencies across regions and business units.
- Improved HR scalability by allowing employee support volumes to grow without proportionally increasing HR headcount.
Employee experience
- Employees received instant, personalized responses through a multilingual AI assistant instead of waiting for manual HR assistance.
- Field workers, engineers, and office employees accessed the same trusted HR information regardless of their location, language, or work schedule.
- Routine HR interactions became faster, more consistent, and more accessible, improving the overall employee self-service experience across the organization.
Strategic value on Databricks
- Established a governed enterprise HR knowledge foundation, consolidating HR policies, employee documentation, compliance materials, and AI agents within a single Databricks Lakehouse.
- Ensured always-current HR guidance through Databricks Vector Search, allowing the AI assistant to automatically retrieve the latest approved HR policies without model retraining.
- Embedded enterprise-grade governance and compliance through Unity Catalog, AI Gateway, audit logging, and Human-in-the-Loop workflows, enabling the solution to operate securely with sensitive employee information.
- Created a scalable AI foundation that enables the organization to extend beyond HR self-service into additional enterprise AI use cases, including IT support, finance, procurement, and internal knowledge assistants.
Closing remarks
Modernizing HR operations requires more than deploying an AI assistant – it requires building a governed HR automation solution that can securely scale across a distributed enterprise workforce. By partnering with GEM, the client transformed fragmented HR knowledge into an intelligent employee self-service experience that delivers consistent, multilingual, and policy-grounded support around the clock.
Built on the Databricks Data Intelligence Platform, the HR automation solution reduced HR back-office effort by more than 80%, improved employee access to HR services across power generation facilities, field operations, and regional offices, and established a trusted AI foundation for future enterprise automation. Beyond solving today’s HR challenges, the solution provides a scalable platform for extending governed AI into additional business functions while maintaining the security, compliance, and operational resilience required by the energy and utilities industry.
Discover another AI transformation success story: Intelligent shipper and carrier matching platform
