We continued to fortify our cyber security approach during the year, delivering a comprehensive action plan to address regulatory compliance, identity and access management, data protection, incident response and recovery, and enterprise standards and processes. We have introduced cyber security considerations into enterprise-wide project management practices, complementing education activities to help employees understand their important role in maintaining security.

We are continuing to increase our data centre resilience to both physical and cyber-related threats by modernising our technology infrastructure, improving business continuity plans and simplifying operations by consolidating data centres into key locations.

During the year we replaced legacy system integration technology with a modern solution. This improved the synchronisation process and data consistency between systems for customer data.

As result, frontline teams can now access the latest customer information when planning and managing outages. The change also allowed the hazard management process to be optimised, and improved our ability to manage high severity customer and premises hazards. Additionally, we can now reliably send real-time surveys to customers following interactions, to better understand their experiences.

This change supports improved safety, customer data security and customer experiences.

Essential Energy is exploring artificial intelligence (AI) to accelerate the digital transformation and deliver enhancements to safety, productivity and the customer experience.

For corporate functions, we have deployed Microsoft Copilot to enable improved productivity and encourage innovation for improved services.

For field teams, we successfully piloted a computer vision model to assist the Asset Review team, as well as virtual assistants to provide conversation-based support for Asset Inspectors. The computer vision model can identify assets exhibiting defects, increasing skilled resource capacity by enabling the Asset Review team to focus on defect validation and classification.