Challenge 1
The team developed an AI-enabled risk management solution that integrates SME heuristics with automated evaluation to improve the quality and actionability of project risk registers. The approach combines Microsoft Power Platform components with LLM-driven analysis to identify weak risks and mitigations, prioritise critical issues, and support continuous learning through SME feedback.
Please be aware that this content was generated follwing an automated review so may not be perfectly accurate; refer to the original challenge brief and team files for authoritative information
Earlier identification of weak or poorly defined risks; improved mitigation quality through structured AI and SME review; more consistent risk language across registers; faster and more informed decision-making supported by live dashboards.
Ai Risk Evaluator_Group 1B_Ministry of Data_23.10.2025_V01.docx: Executive summary and architecture description of the AI-driven risk evaluation solution.Risk Management App - User Guide.docx: User guide explaining how to capture risks, review AI evaluations, provide SME feedback, and use dashboards.SME Heuristics Word Analysis.docx: Detailed analysis and categorisation of SME heuristics used to assess risk and mitigation quality.
team: AI Risk Evaluator members: tbc topics: solution-centre, hack26, challenge1, microsoft-excel, dataverse, power-apps, power-automate, copilot-studio, power-bi, large-language-models, risk-management, heuristics, tacit-knowledge, data-quality, project-risk, decision-support, analytics technologies: microsoft-excel, dataverse, power-apps, power-automate, copilot-studio, power-bi, large-language-models