Case Study: GMCT Enterprise AI Solution for Rights of Internment Transfers

Background

The Greater Metropolitan Cemeteries Trust (GMCT) manages 19 active cemeteries across Melbourne, covering 1,000 hectares of land and serving diverse communities with historical and contemporary burial sites. A key responsibility under the Cemeteries and Crematoria Act is the accurate and perpetual maintenance of records, including the management of Rights of Internment (ROI) transfers. This process, which involves intricate legal, regulatory, and procedural requirements, has traditionally been labour-intensive, reliant on a small team, and prone to bottlenecks.

To address these challenges, GMCT partnered with Digital Frontier Partners (DFP) to develop an enterprise AI solution designed to streamline ROI transfers, enhance compliance, and improve customer service delivery.

Objectives

The AI initiative was designed to:

• Reduce key person dependencies.
• Expedite the processing of ROI transfers.
• Improve regulatory compliance.
• Enhance customer experience through consistent and accurate responses.
• Lay the foundation for scalable AI use cases within GMCT.

Implementation Process

Data Gathering

• Key documentation, FAQs, and internal policies were identified and integrated into the AI model.
• Historical contact centre queries were used to provide real-world scenarios for training and validation.

Model Training and Testing

• A dataset of 40 contact centre questions was used to train the AI on common and complex queries.
• Iterative testing ensured accurate, concise, and contextually relevant responses.

Usability Optimisation

• Initial responses were refined to provide concise summaries with optional detailed expansions, improving usability for staff and customers.

Regulatory Compliance

• The AI solution was developed within a secure Azure environment, ensuring data sovereignty and compliance with state and federal regulations, including privacy and data protection mandates.

Outcomes and Benefits

Operational Efficiencies

• Streamlined Processes: The AI reduced bottlenecks in ROI transfer workflows, enabling faster resolutions.
• Scalable Knowledge Repository: Centralised AI knowledge reduced reliance on specialist staff.

Customer Experience Improvements

• Consistent Responses: Families received accurate and reliable information across all interactions.
• Self-Service Potential: Future chatbot integration could allow families to access necessary information independently, reducing back-and-forth communications.

Regulatory Assurance

• Adherence to stringent regulatory frameworks was ensured through secure data management and alignment with government guidelines.

Foundation for Future Growth

• The proof of concept validated AI’s potential for additional use cases, including supporting outdoor staff with mobile devices and exploring historical data using natural language queries.

Challenges

• Data Preparation: Identifying and structuring relevant documents and FAQs for AI training.
• Usability Testing: Ensuring responses were accessible and actionable for staff and customers.
• Change Management: Building internal confidence in adopting AI technology for critical workflows.

Lessons Learned

1. Start Small: A targeted proof of concept enabled GMCT to validate AI’s feasibility and value incrementally.
2. Partner Collaboration: Working with experienced solution partners complemented GMCT’s internal capabilities.
3. User-Centric Design: Focusing on usability ensured the AI’s outputs were practical and effective.

ROI and Future Projections

• Time Savings: Significant reductions in processing times for ROI transfers, freeing up staff for other critical tasks.
• Cost Efficiency: Automating knowledge-intensive processes reduces reliance on manual expertise, minimising training costs and mitigating risks.
• Customer Satisfaction: Improved service delivery and reduced response times enhance GMCT’s reputation and customer trust.
• Scalability: The AI solution sets the stage for broader applications, including advanced record management, chatbot integration, and mobile support for field staff.

Conclusion

GMCT’s enterprise AI solution showcases the transformative potential of targeted AI applications in public sector organisations. By addressing a complex and essential process, the AI initiative not only enhances operational efficiency but also positions GMCT as a forward-thinking leader in leveraging technology for community service. The ongoing roadmap promises continued innovation and value generation for both the organisation and its stakeholders.