Projects shortlisted for Canada Public Service Data/AI Challenge
Four projects focusing on how to better use data or artificial intelligence in government have been shortlisted for the next stage of the Public Service Data/AI Challenge in Canada.
The shortlisted projects have been developed from ideas submitted by federal public servants in Canada on how government can improve its use of data and artificial intelligence, with the ideas then developed by teams of public service volunteers, supported by challenge knowledge partners IBM, Dell and NVIDIA.
The shortlisted projects are:
- 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.
- 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.
- 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.
- 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.
Read more: Data Challenge serves as an engine of innovation for Canada’s public services
Congratulations to ‘four exceptional finalists’
The Public Service Data/AI Challenge is run by Global Government Forum in partnership with Natural Resources Canada and Statistics Canada.
Elise Legendre, the chief data officer at the Agriculture and Agri-Food Canada and the chair of the judges of the Public Service Data/AI Challenge in Canada, said the “challenge helps the Government of Canada to understand and explore further opportunities to improve how we use data and AI to transform public services”. She added: “I want to thank all the teams involved in the shortlisted projects – and those who worked on all the projects on the longlist – for their work in helping drive the transformation of the Government of Canada.”
In a statement congratulating the shortlisted projects, IBM said there were “four exceptional finalists”, whose ideas will now be developed further ahead of a final on December 9 as part of the AccelerateGov conference.
The statement to the teams added: “Your innovative ideas reflect a deep commitment to the best interests of Canada and Canadians, and it’s inspiring to see how collaboration has been at the heart of this journey – within your teams, with the organizers, and with our valued partners like IBM, NVIDIA, and Dell. It’s this spirit of partnership that drives meaningful progress and innovation.
“To the finalists, the challenge now is to bring your ideas to life in time for the final on December 9. We can’t wait to see how you take your concepts to the next level and demonstrate the impact they could have on the lives of Canadians.”
In a message to the four projects that didn’t make it from the longlist to the shortlist, IBM added: “For the teams who didn’t make it through this time, don’t let today define the future of your ideas. Keep pushing forward, because your work holds the potential to make a real difference. At IBM, we believe that innovation thrives when we persevere and continue to build on our vision.
“At its core, this challenge is about creating solutions that matter—leveraging data and technology to address critical issues and improve outcomes for citizens. IBM Canada is proud to support initiatives like this that encourage collaboration, creativity, and impact. Together, we are shaping a smarter future for Canada.”
In its statement to teams, NVIDIA said it was “proud to support the impressive work of the four shortlisted teams at the Public Service Data/AI Challenge, as they apply advanced AI techniques to tackle real-world challenges”.
It added: “Their projects showcase the transformative potential of AI when applied to practical, high-impact problems. By harnessing the power of AI, these teams are developing innovative, user-centric solutions designed to meaningfully enhance productivity across Canada’s public sector.”
Read more: Energy efficiency tool wins Canada’s second Public Service Data Challenge
The history of the Data Challenge
This is the third year of the Data Challenge being run in the Canadian public service. In the first year, the winning team proposed using ChatGPT to transform the agriculture department’s search function. The Agpal Chat system is now up and running, improving access to public services for farmers and agricultural businesses across Canada.
In the challenge’s second year, the winning project proposed combining two NRCan datasets to understand how different interventions affect domestic energy efficiency. The team behind it is now working on delivering that project – helping public funders and homeowners to cut their energy bills and carbon emissions.
Stephen Burt, the chief data officer of Canada and Public Service Data Challenge champion, said the programme was designed to put public servants in the driving seat “and help you to develop your skills and careers while improving services and the tools available to public servants”.
He added: “The government wants to empower you, our colleagues, to put forward your ideas, and to take the most promising ones forward into implementation.”
Read more: Delivery driver: how the Canadian Data/AI Challenge makes data dreams come true
About Richard Johnstone
