Australian Human Rights Commission automates records management with AI
The Australian Human Rights Commission (AHRC), Australia's national human rights institution, faced significant challenges with manual records management, such as document duplication, lost files, and compliance inefficiencies. To address these, AHRC implemented an automated Electronic Document and Records Management System (EDRMS) on SharePoint in partnership with RecordPoint, using their AI and machine learning tools. The solution replaced manual processes, using a combination of minimal rule trees and natural language processing-based machine learning models for record classification. Staff no longer had to manually classify documents, leading to higher user adoption and an immediate reduction in errors. Key components of the project included a new information governance framework, extensive collaboration during development, and careful change management planning. The AI model was initially trained on manually classified data and refines its predictions whenever documents are updated, improving classification performance over time. The Commission chose a configuration-over-customization approach for seamless integration, user experience, and future upgradeability. The project yielded strong outcomes: better information management practices, a 5% productivity increase, improved compliance, reduced responses to Freedom of Information (FOI) requests, lower storage costs, streamlined collaboration, and overall improved digital transformation within a regulatory setting. Other agencies can adopt the approach for similar benefits. Cost savings versus traditional EDRMS solutions were significant, and AHRC became a leader in Australian government adoption of AI-driven records management.
- Organization
- Australian Human Rights Commission
- Industry
- Public Sector
- Location
- Australia
- Published
- October 2021
Reported outcomes
+5%
productivityProductivity & throughput
Strategic outcomes
Catalog median for productivity & throughput deployments: +45% across 225 reported metrics. Compare benchmarks →
Primary read
Use case focus
Showing 3 of 3
- 1Automated Document Classification and Management
- 2AI-driven Electronic Records Management
- 3FOI Request Processing Automation
- Duplicate, lost, and poorly organized documents hampered records management.
- Manual classification processes were time-consuming and error-prone.
- Limited funding and technology made traditional EDRMS solutions unviable.
- Difficulty in searching, retrieving, and complying with records management regulations.
- Increased administrative burden on staff detracted from core mission work.
- Implementation of an AI-driven EDRMS (Records365) on SharePoint and Office 365.
- Utilized minimal rules trees and machine learning (natural language processing) to classify and manage records automatically.
- Configuration-based integration with RecordPoint, focusing on usability and future upgrades.
- Information governance and security model overhaul, including user training and change management support.
- Productivity increased by at least 5% for staff handling records.
- Accuracy of document classification improved beyond manual classification capabilities.
- Reduced costs associated with physical and digital storage (annual digital/physical storage savings).
- Faster, more accurate responses to FOI requests and improved agency compliance reporting.
- Higher overall user satisfaction and collaboration across the organization.
Architecture
The solution is built on SharePoint and Office 365, integrating RecordPoint's Records365 EDRMS platform. It combines minimal rules-based classification with a custom machine learning model leveraging natural language processing. The system migrates, classifies, and manages records automatically, with continuous training and improvement. Search and security layers ensure compliance and ease of access, and Power BI is used for analytical reporting. Change management and end user training support adoption.
Implementation partners1
Sources & evidence1
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