AI for Strategic Decision Making 2: Planning with AI Insights

This micro-course can be applied toward the UBC Certificate in AI Skills Accelerator for IT, Digital and Enterprise Systems Professionals and is the the proficiency level 2 micro-course in the AI for Strategic Decision Making track.

Building on foundational AI business solution knowledge, this proficiency level micro-course empowers IT professionals to design, implement and manage comprehensive AI-powered business solutions while developing practical skills in solution architecture, system integration and project management.

This micro-course is designed for IT professionals in managerial, project management and leadership roles.

By the end of this course, you will be able to:

• Evaluate AI’s strategic impact: analyze the benefits, risks, and ethical implications of deploying AI in strategic decision making, diagnose data quality and over reliance issues, and design mitigation strategies that protect business outcomes
• Engineer LLM tool calling workflows: write system prompts, define JSON function schemas, and implement the two step “LLM → tool → LLM” pattern while controlling token usage, latency, cost, and secure credential management
• Apply Retrieval Augmented Generation (RAG): build end to end pipelines that embed proprietary documents or embeddings into LLM responses, and compare RAG with function calling for real time versus static knowledge needs
• Select an AI architectural pattern using a Build vs Buy framework: differentiate embedded, platform based, and bespoke AI solutions, assess data sensitivity, strategic differentiation, speed to market, and talent/cost constraints, and choose the optimal architecture for a given use case
• Incorporate Indigenous data sovereignty principles: integrate OCAP and CARE frameworks (and related legal sources such as UNDRIP, Section 35, PIPEDA) into AI enhanced telemetry pipelines, applying consent tags, lineage metadata, role based access, and privacy by design controls
• Develop comprehensive AI governance and risk mitigation policies: establish governance artefacts (MOUs, DPIAs, audit logs), manage credential lifecycles, monitor token budgets, address vendor lock in and service availability risks, and implement continuous compliance and operational monitoring for AI systems

Platform and tool selection varies and is regularly updated to reflect current industry trends. Students can expect to interact with:

• Enterprise integration platforms (MuleSoft, Microsoft Logic Apps)
• AI development platforms (Microsoft Power Platform, Google Cloud AI)
• Data pipeline tools (Apache Airflow, Azure Data Factory)
• Testing frameworks and quality assurance tools
• Performance monitoring and analytics platforms

Course outline

• Module 1: Advanced AI solution architecture and design patterns
• Module 2: System integration and API management
• Module 3: Data pipeline design and management
• Module 4: AI solution testing and quality assurance
• Module 5: Change management and user adoption strategies
• Module 6: Performance monitoring and optimization

The course outline may be subject to change as AI evolves and the course is updated to reflect the latest content.

How am I assessed?

You will be assessed on successfully completing weekly activities, including exercises, quizzes, applied case study projects (based on real-life scenarios) and your contributions to discussion posts. These activities are marked using a proficiency scale, and your instructor provides you informal feedback during live online sessions.

While you are not assessed on your attendance of the live online sessions, we encourage you to attend so you can learn and interact with your instructor and other participants. All sessions are recorded in case you miss one.

This micro-course operates on a pass/fail basis. You must achieve an overall grade of 70% or greater to pass and be eligible to earn the UBC Certificate in AI Skills Accelerator for IT, Digital and Enterprise Systems Professionals.

Expected effort

Expect to spend approximately 14 hours per week per course completing all learning activities, including attending live sessions online.

Requisites

Completion of AI for Strategic Decision Making 1: Introduction or equivalent AI knowledge.

Course format

This 100% online part-time program consists of instructor-supported real-time classes combined with independent study. 

Each micro-course will consist of a weekly virtual class taught by subject matter experts and a high degree of personal engagement and interactivity. Live sessions are recorded. Outside of class, you can access online materials on your own time.

One business day before the micro-course start date, we'll email you step-by-step instructions for accessing your micro-course.