AI Infrastructure

Audience: Executive Leadership

Duration: 0.5 Day

Delivery: Virtual or in-person

This module explains the infrastructure, data engineering, and model‑management foundations required to build reliable, secure, and scalable AI capabilities within the Government of Canada and defence environments.

• GoC has a data engineering issue! — why federal departments struggle with fragmented data, legacy systems, inconsistent pipelines, and limited interoperability, and how these constraints directly limit AI readiness and operational advantage.

• Model management — the lifecycle practices needed to deploy, monitor, secure, version, and retire AI models responsibly, including drift detection, auditability, and defence‑grade assurance.

• Data as fuel for AI engines — how data ingestion, cleaning, transformation, and orchestration pipelines create the reliable, high‑quality data flows that AI systems depend on.

• Let’s talk Microsoft / Google / AWS / Open Source — the strengths, limitations, and strategic considerations of major cloud and open‑source ecosystems, including sovereignty, security, interoperability, and alignment with GoC digital standards.

• Visualization & reporting — how dashboards, reporting tools, and analytical visualizations translate complex data and model outputs into clear, actionable insight for commanders, executives, and operational teams.