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The Longlist

Around 150 of you sent your ideas into the Public Service Data Challenge, and the judges long-listed the eight most promising for development by interdisciplinary, cross-departmental project teams: these ideas are outlined below.

Many thanks to everyone who submitted an idea: the quality of your proposals was very high, clearly demonstrating the expertise, inventiveness, enthusiasm and commitment of Canada’s federal workforce.

Below you can read short summaries of the long-listed ideas.

Language Competency Evaluation and Training Tool

Language Competency Evaluation and Training Tool

Leveraging AI to enhance second-language training for public service employees, this tool provides real-time assessment, personalized feedback, and adaptive learning. By integrating databases from the Canada School of Public Service and using AI to generate customized practice questions, it allows employees to target their weaknesses efficiently. The AI tutor offers explanations and examples, reducing training costs and improving success rates on second-language evaluations.

Submitted by Ion-Mircea Ghinda at Global Affairs Canada

Digital Twins for Smarter Infrastructure Management

Digital Twins for Smarter Infrastructure Management

The creation of a Digital Twin of the Samuel De Champlain Bridge and highway corridor will be used to monitor structural health, traffic flow, and environmental impact using real-time data. By integrating AI-powered analytics with geospatial data, this virtual model will enhance decision-making, enable predictive maintenance, and improve emergency response planning. The initiative lays the groundwork for broader applications in federal infrastructure projects, fostering innovation and intergovernmental collaboration.

 

Submitted by Kate Burnett-Isaacs at Housing, Infrastructure and Communities Canada

Application Processing Tool to support Indigenous Children

Application Processing Tool to support Indigenous Children

A generative AI solution to streamline the intake and triaging of applications submitted under Jordan’s Principle, which ensure First Nations children receive essential services. The AI tool will extract and categorize key information from diverse document formats, reducing processing times and manual workload. By improving efficiency and compliance with Canadian Human Rights Tribunal mandates, this solution enhances support for Indigenous children while providing a scalable model for broader service delivery.

 

Submitted by Beni Vand at Indigenous Services Canada

“Tell-Us-Once” Approach for National Trade Corridors

“Tell-Us-Once” Approach for National Trade Corridors

This initiative introduces an AI-driven solution to simplify data-sharing across national trade corridors, reducing redundant submissions and improving interoperability between government platforms. By standardizing data formats and leveraging real-time validation, the system will enhance efficiency, lower administrative burdens for industry stakeholders, and provide government agencies with better-quality trade data. This project supports a more agile and resilient supply chain, strengthening Canada’s trade competitiveness.

 

Submitted by Erika-Kirsten Easton at Transport Canada

Financial Forecasting for Government Spending

Financial Forecasting for Government Spending

Building on successful AI-driven forecasting models used at Housing, Infrastructure and Communities Canada, this tool aims to transform financial planning across federal departments. By automating and improving Grants and Contributions forecasting, the model enhances accuracy, reduces processing time by 66%, and minimizes budget lapses—potentially saving billions in taxpayer dollars. Scalable across departments, the tool modernizes financial decision-making, ensuring smarter and more efficient government spending

 

Submitted by Pierre Zwiller-Panicz at Housing, Infrastructure and Communities Canada

Enhanced Job Classification Evaluation in the Federal Public Service

Enhanced Job Classification Evaluation in the Federal Public Service

The federal government’s classification system assesses job descriptions to determine salary levels, but the manual process is time intensive. This project proposes testing an AI chatbot trained on thousands of job descriptions and classification standards to support advisors in analyzing and summarizing job evaluations. The tool aims to improve efficiency while maintaining human oversight, potentially streamlining classification processes across government.

 

Submitted by Brianna Smrke at Treasury Board of Canada Secretariat

Metadata and Meta-Tagging for Scientific Data Management

Metadata and Meta-Tagging for Scientific Data Management

This initiative leverages AI to automate metadata creation and enhance meta-tagging, streamlining scientific data management and improving discoverability. AI will generate standardized metadata from research documents and datasets while refining search functionality through intelligent tagging, addressing gaps like incomplete location-based information. By reducing manual burden and ensuring datasets are properly catalogued, this approach enhances accessibility on platforms like the Open Science and Data Platform. Implementing AI-driven metadata solutions across departments will foster collaboration, reduce duplication, and maximize the value of government-funded research.

 

Submitted by Terence Hams and Mariia Stepaniuk at Natural Resources Canada

Risk and Requirements Advisor for Government Projects

Risk and Requirements Advisor for Government Projects

This tool will enhance project planning by identifying potential risks and improving requirements management across government projects. By analyzing historical project data, AI will provide proactive risk assessments and mitigation strategies, while also improving requirements gathering through NLP-driven extraction and automated quality checks. This approach will reduce costly project delays, improve decision-making, and ensure more effective resource allocation. Standardizing risk and requirements management with AI-driven insights will lead to more successful project outcomes and better public service delivery.

Submitted by Nicolas Martinez and Brandon Ferguson at Public Services and Procurement Canada, and Hoda Khalil at Department of National Defence