AI initiative registry

Every initiative listed in the registry can be consulted here, without an account. Each record shows its progress, its milestones and the history of its decisions. Requests still under triage do not appear: they join the registry once reviewed.

Automation and Decision Support

AI that helps make or automate decisions, often using rules, predictions, or pattern recognition.

What is “Automation and Decision Support”?

This category includes AI systems that analyze structured data, recognize patterns, and support or automate decision-making processes. These systems are often built around predictions, classifications, or recommendations and are used to improve operational efficiency, mitigate risks, or optimize outcomes.

Automation and Decision Support
Subcategory	Description	Examples
Predictive analytics	Using data to forecast trends or risks	Fish stock modeling, equipment failure prediction
Prescriptive analytics	Recommending actions	Conservation policy optimization, vessel routing
Robotic Process Automation (RPA) + AI	Automating rule-based digital tasks with AI augmentation	Document classification, triaging emails
Optimization	Finding the best outcome under constraints	Resource allocation, scheduling patrols

Key indicator: If the AI’s goal is to make or inform a decision, suggest a course of action, or automate a rule-based task — it likely fits here.
Focus: Pattern recognition, statistical modeling, optimization, or rule-based logic, often on structured data (spreadsheets, telemetry, logs).

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54 current initiative(s)

AI initiative registry
ID	AI Initiative	Stage	Description	Sector	Region	AI Bucket	SME
27	Turn on AI Auto labeling on all M365 documents and communications channels	Ideation	Our E5 M365 licences grant access to AI based tools in Purview to automatically categorized documents and set labels accordingly. Model tra...	Chief Digital Officer	Quebec	Automation and Decision Support	Bussieres, Martin
108	The development of rapid multiplex qPCR for the detection and quantification of three parasites MSX, SSO, Dermo of oysters (Crassostrea virginica) and MSX single-cell whole genome sequencing using long read sequencing platform’	Pilot	This 2-year project aims to enhance the disease diagnostic services provided to the shellfish aquaculture industry by improving the methods...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
75	Study on the use of Artificial Neural Networks to Predict the Return Timing and Northern Diversion Rate for Migrating Fraser River Sockeye Salmon	Ideation	The Machine Learning feasibility study compliments the statistical approach by asking whether Artificial Intelligence (AI) methods can be de...	Ecosystems and Oceans Science	Pacific	Automation and Decision Support	Thomson, Richard
69	Species distribution modeling	Pilot	Species distribution models for various coral/sponge/groundfish Random Forests	Ecosystems and Oceans Science	Pacific	Automation and Decision Support	Rooper, Chris
8	SAP AI Agent	Ideation	SAP AI Agent to validate financial transaction coding with invoices	Chief Digital Officer	National Capital Region	Automation and Decision Support	Gardner, Leigh
177	Resume Bank Analysis	Ideation	Resume bank analysis: summarizing candidates resumes in our digital skills bank to provide consistent summaries (remove biases) and potentia...	Strategic Policy	National Capital Region	Automation and Decision Support	Kiefl, Richard
17	Recruitment and staffing tools	Ideation	Recruitment and staffing tools (Mark Jarvis) (existing agents created by Microsoft to be explored further)	Chief Digital Officer	National Capital Region	Automation and Decision Support	Gardner, Leigh
178	Records of decision for governance committees supporting the CDO	Ideation	Records of Decision for Governance Committees Supporting the Chief Digital Office: Leveraging the transcript function in Microsoft Teams to...	Strategic Policy	National Capital Region	Automation and Decision Support	Kiefl, Richard
31	Quality control of oceanographic data - Maritimes Region	Pilot	The goal of the project is to assist in the processing and quality control of CTD (oceanographic) data by leveraging machine learning models...	Strategic Policy	National Capital Region	Automation and Decision Support	Croft, Lee
117	PolyDocs: Format and Translate for CSAS	Production	A modular, bilingually-optimized (EN/FR) application that automates the formatting, quality assurance, and standardization of complex Word d...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Carr, Kevin
13	PoC in Power Apps, Power Automate, and SharePoint	Ideation	PoC in Power Apps, Power Automate, and SharePoint (Mark Jarvis) to have an efficient helpdesk; AI to review questions and predict templates...	—	National Capital Region	Automation and Decision Support	Gardner, Leigh
135	PII & Sensitivity Scores	Pilot	Determines the sensitivity of the content of a document based on a trained model and allows for the redaction of the sensitive material in t...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
54	PII & Sensitivity Scores	Ideation On hold On hold	Determines the sensitivity of the content of a document based on a trained model and allows for the redaction of the sensitive material in t...	Programs Sector	Pacific	Automation and Decision Support	Quan, Eric
186	Paper Buyer Slips	Pilot	Automatically process 180K paper slips annually Solution being developed in region to assist Statistics team in batch-scanning and processin...	Indigenous Affairs, Aquaculture and Governance	Gulf	Automation and Decision Support	Dupuis, Marc
15	MyGCHR Phoenix analysis	Ideation	MYGCHR Phoenix analysis tool (Mark Jarvis) to flag incorrect records and recognize future incorrect entries to help cleanup pay files	Chief Digital Officer	National Capital Region	Automation and Decision Support	Gardner, Leigh
45	MyGCHR – Phoenix analysis tool	Ideation	Pro B data would be needed, but feed MyGCHR and Phoenix records, but flag those that are incorrect in the hopes of training the AI to recogn...	Human Resources and Corporate Services	National Capital Region	Automation and Decision Support	Gardner, Leigh
56	Method Recommendation Engine	Ideation	A large language model reviews a scientist’s objective for collecting data in the field and based on the criteria, the model will provide th...	Programs Sector	Pacific	Automation and Decision Support	Quan, Eric
137	Method Recommendation Engine	Pilot	A large language model reviews a scientist’s objective for collecting data in the field and based on the criteria, the model will provide th...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
201	Maximize detections with AI of the aquatic autonomous environmental DNA (eDNA) sampler	Ideation	This Canadian apparatus provides detections of aquatic species through a standardized and reproducible method. Algorithms of AI analyze data...	—	National Capital Region	Automation and Decision Support	Winegardner, Amanda
133	LLM Document Extraction - Prompt Engineering to Retrieve Relevant Information	Pilot	Using LLM to extract key information from documents with multiple templates using prompt engineering approaches. These results are reviewed...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
3	Labels Pilot	Pilot	We are looking into using Labels back end for smart labels as well as a free copilot agent for the departement to use in order to validate a...	Chief Digital Officer	National Capital Region	Automation and Decision Support	Bartoli, Saul
113	Improving forecasting for high-priority ports	Pilot	Research into feasibility of improving accuracy and timeliness of short-term forecasts for coastal regions by combining traditional and AI m...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
99	Improved freshwater runoff modelling in Eastern Canada to drive ocean models	Pilot	Use Neural Networks to post-process streamflow simulations from the WRF-Hydro model, improving their agreement with observational data. Thes...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
98	Guidance on Optimal Timing for Environmental DNA (GOTeDNA)	Pilot	Provide guidance on optimal eDNA sampling periods and standardized sampling procedures for assessing and monitoring coastal species using eD...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
246	GeoAI	Ideation	Overview: Potential GeoAI‑Impacted Programs and Processes GeoAI (the integration of geospatial data, AI, and machine learning) is being exp...	Chief Digital Officer	Not region specific	Automation and Decision Support	Merner, Erick

27
Turn on AI Auto labeling on all M365 documents and communications channels
Our E5 M365 licences grant access to AI based tools in Purview to automatically categorized documents and set labels accordingly. Model training would require attention of an Security/IM expert to make perfect. We may want to create specific AI specific labels to avoid conflicts with officials ones.

Ideation Chief Digital Officer Automation and Decision Support
108
The development of rapid multiplex qPCR for the detection and quantification of three parasites MSX, SSO, Dermo of oysters (Crassostrea virginica) and MSX single-cell whole genome sequencing using long read sequencing platform’
This 2-year project aims to enhance the disease diagnostic services provided to the shellfish aquaculture industry by improving the methods for detecting economically important Oyster parasites, enhance understanding of Multinucleate Sphere Unknown X (MSX) virulence dynamics, and support the creation of new vaccine in investigating future outbreaks and modeling through machine learning.

Pilot Ecosystems and Oceans Science Automation and Decision Support
75
Study on the use of Artificial Neural Networks to Predict the Return Timing and Northern Diversion Rate for Migrating Fraser River Sockeye Salmon
The Machine Learning feasibility study compliments the statistical approach by asking whether Artificial Intelligence (AI) methods can be developed to predict salmon behaviour as functions of ocean conditions. classical machine learning models, including linear regression, Ridge regression, and Random Forest

Ideation Ecosystems and Oceans Science Automation and Decision Support
69
Species distribution modeling
Species distribution models for various coral/sponge/groundfish Random Forests

Pilot Ecosystems and Oceans Science Automation and Decision Support
8
SAP AI Agent
SAP AI Agent to validate financial transaction coding with invoices

Ideation Chief Digital Officer Automation and Decision Support
177
Resume Bank Analysis
Resume bank analysis: summarizing candidates resumes in our digital skills bank to provide consistent summaries (remove biases) and potentially providing side by side comparisons of candidate resumes or searching for skills

Ideation Strategic Policy Automation and Decision Support
17
Recruitment and staffing tools
Recruitment and staffing tools (Mark Jarvis) (existing agents created by Microsoft to be explored further)

Ideation Chief Digital Officer Automation and Decision Support
178
Records of decision for governance committees supporting the CDO
Records of Decision for Governance Committees Supporting the Chief Digital Office: Leveraging the transcript function in Microsoft Teams to formalize records of decision and streamline follow-up on action items.

Ideation Strategic Policy Automation and Decision Support
31
Quality control of oceanographic data - Maritimes Region
The goal of the project is to assist in the processing and quality control of CTD (oceanographic) data by leveraging machine learning models to predict quality flags for the CTD data products generated by Maritimes region, enabling faster data processing by reducing manual burden. Initial explorations have been conducted to investigate transferability of existing quality control models from Pacific region. Based on investigation results, new models will be trained specific to Maritimes region. Client: Maritimes Region - Ocean Data

Pilot Strategic Policy Automation and Decision Support
117
PolyDocs: Format and Translate for CSAS
A modular, bilingually-optimized (EN/FR) application that automates the formatting, quality assurance, and standardization of complex Word documents to meet Government of Canada publishing requirements. The tool orchestrates a highly configurable, low-code assembly line that handles deep document cleanup (resolving fragmented text, localizing punctuation/number conventions, and rebuilding tables of contents), applies localized terminology glossaries, and reduces file sizes for accessibility.

Production Ecosystems and Oceans Science Automation and Decision Support
13
PoC in Power Apps, Power Automate, and SharePoint
PoC in Power Apps, Power Automate, and SharePoint (Mark Jarvis) to have an efficient helpdesk; AI to review questions and predict templates and carry out actions (e.g., reset accounts, forward others to MyPay etc.)

Ideation Automation and Decision Support
135
PII & Sensitivity Scores
Determines the sensitivity of the content of a document based on a trained model and allows for the redaction of the sensitive material in the document.

Pilot Ecosystems and Oceans Science Automation and Decision Support
54
PII & Sensitivity Scores
Determines the sensitivity of the content of a document based on a trained model and allows for the redaction of the sensitive material in the document. Presidio

Ideation On hold Programs Sector Automation and Decision Support
186
Paper Buyer Slips
Automatically process 180K paper slips annually Solution being developed in region to assist Statistics team in batch-scanning and processing paper slips.

Pilot Indigenous Affairs, Aquaculture and Governance Automation and Decision Support
15
MyGCHR Phoenix analysis
MYGCHR Phoenix analysis tool (Mark Jarvis) to flag incorrect records and recognize future incorrect entries to help cleanup pay files

Ideation Chief Digital Officer Automation and Decision Support
45
MyGCHR – Phoenix analysis tool
Pro B data would be needed, but feed MyGCHR and Phoenix records, but flag those that are incorrect in the hopes of training the AI to recognize future incorrect entries and to help clean up pay files for employees. P&C is in negotiation currently with PSPC to ‘own’ our backlog of Phoenix cases, so this could be a big help.

Ideation Human Resources and Corporate Services Automation and Decision Support
56
Method Recommendation Engine
A large language model reviews a scientist’s objective for collecting data in the field and based on the criteria, the model will provide the best procedure to use for their work

Ideation Programs Sector Automation and Decision Support
137
Method Recommendation Engine
A large language model reviews a scientist’s objective for collecting data in the field and based on the criteria, the model will provide the best procedure to use for their work

Pilot Ecosystems and Oceans Science Automation and Decision Support
201
Maximize detections with AI of the aquatic autonomous environmental DNA (eDNA) sampler
This Canadian apparatus provides detections of aquatic species through a standardized and reproducible method. Algorithms of AI analyze data from buoy-mounted sensors to determine optimal sampling windows, such as the presence of toxic phytoplankton bloom, and to perform quality assurance on sampling metadata.

Ideation Automation and Decision Support
133
LLM Document Extraction - Prompt Engineering to Retrieve Relevant Information
Using LLM to extract key information from documents with multiple templates using prompt engineering approaches. These results are reviewed by SMEs to ensure accuracy and relevancy.

Pilot Ecosystems and Oceans Science Automation and Decision Support
3
Labels Pilot
We are looking into using Labels back end for smart labels as well as a free copilot agent for the departement to use in order to validate a user's classification. if we could fund the "query" fund for the user community we could point the Free agent to consume DFO specific Information on Information Classification. as for the other option we will need to ensure we have items to feed the machine learning.

Pilot Chief Digital Officer Automation and Decision Support
113
Improving forecasting for high-priority ports
Research into feasibility of improving accuracy and timeliness of short-term forecasts for coastal regions by combining traditional and AI modelling methods.

Pilot Ecosystems and Oceans Science Automation and Decision Support
99
Improved freshwater runoff modelling in Eastern Canada to drive ocean models
Use Neural Networks to post-process streamflow simulations from the WRF-Hydro model, improving their agreement with observational data. These neural networks are applied as a downstream calibration step. Builds synergy between traditional calibration methods and modern AI techniques in hydrologic modeling.

Pilot Ecosystems and Oceans Science Automation and Decision Support
98
Guidance on Optimal Timing for Environmental DNA (GOTeDNA)
Provide guidance on optimal eDNA sampling periods and standardized sampling procedures for assessing and monitoring coastal species using eDNA. GOTeDNA, a centralized interactive online tool currently in development, will report/visualize trends in spatio-temporal eDNA distributions.

Pilot Ecosystems and Oceans Science Automation and Decision Support
246
GeoAI
Overview: Potential GeoAI‑Impacted Programs and Processes GeoAI (the integration of geospatial data, AI, and machine learning) is being explored to enhance decision‑making, efficiency, and service delivery by automating spatial analysis, identifying patterns at scale, and enabling predictive insights. 1. Program and Service Delivery GeoAI can support more targeted, timely, and evidence‑based services by: Identifying spatial patterns in environmental, socio‑economic, or ecological data Prioritizing areas for intervention, monitoring, or investment Improving accessibility and equity of services through location‑based insights Examples Risk‑based prioritization of inspections, monitoring sites, or enforcement activities Predictive habitat or species distribution mapping to support conservation or fisheries management Enhanced situational awareness for emergency response or environmental incidents 2. Operational Efficiency GeoAI enables automation and scalability in routine or data‑intensive operations, reducing manual effort and turnaround times. Examples Automated feature extraction from satellite imagery, aerial photos, or LiDAR (e.g., shoreline change, infrastructure, habitat types) Near‑real‑time monitoring of environmental conditions or operational assets Change detection to flag anomalies or emerging risks Operational Benefits Reduced reliance on manual digitization and visual interpretation Faster updates to spatial products and dashboards More consistent and repeatable analytical outputs 3. Business Processes and Decision Support GeoAI can modernize internal business processes by embedding spatial intelligence into planning, reporting, and governance workflows. Examples Predictive analytics to support long‑term planning and scenario analysis Decision‑support tools that integrate geospatial, operational, and administrative data AI‑assisted data quality assessment and metadata generation Process Impacts Improved transparency and defensibility of decisions Better integration of spatial data across programs and systems Enhanced performance measurement and outcome tracking 4. Cross‑Cutting Opportunities Across all domains, GeoAI supports: Data integration: Linking spatial, temporal, and non‑spatial datasets Scalability: Applying consistent analysis across large geographic areas Innovation: Enabling new analytical questions that were previously impractical

Ideation Chief Digital Officer Automation and Decision Support