Course Overview on AI Transformation Leader
Unlock the business value of AI and lead transformation with clarity and confidence. In this focused one-day AI Transformation Leader course, you’ll gain the practical knowledge and strategic tools to identify valuable AI opportunities, choose the right Microsoft AI solutions, and guide responsible adoption across your organisation, without needing a technical background.
Explore generative AI, Microsoft 365 Copilot, Copilot Studio, Microsoft Foundry, governance, licensing and change management through business-focused examples and a running case study. Ideal for decision-makers and transformation leaders who want to build a secure, responsible and measurable AI strategy while preparing for Microsoft Exam AB-731.
What You Will Learn
By the end of this course, participants will be able to:
- Understand generative AI and how it can create business value.
Identify high-value AI opportunities and match them to business needs. - Explain prompting, grounding, retrieval-augmented generation (RAG), data quality and secure AI.
- Compare Microsoft Copilot Chat, Microsoft 365 Copilot, Copilot Studio, Researcher and Analyst.
- Determine when to buy, extend or build an AI solution.
- Explore Microsoft Foundry and select appropriate Foundry Tools and AI models for different scenarios.
- Apply responsible AI principles, governance controls and human oversight to AI initiatives.
- Establish an AI council, adoption team and champions programme.
- Evaluate licensing, consumption costs, business value and return on investment.
- Create a practical AI adoption plan and prepare for Microsoft Exam AB-731.
Delivery Methods
| Delivery Method | Duration | ||
|---|---|---|---|
| 2 days | Get a Quote | ||
| 2 days | Get a Quote |
Discounts Available
Save up to 10% by booking and paying 10 business days before the course.
Brochure:
Audience
This course is designed for business leaders who guide AI transformation in their organisations:
- Executives, directors and senior managers responsible for business strategy and transformation.
- Business decision-makers evaluating where and how AI can create measurable value.
- Department heads and operational leaders seeking to improve productivity, decision-making and customer experiences with AI.
- Digital transformation, innovation and change-management professionals leading AI adoption.
- IT, data, security, risk and compliance leaders supporting responsible AI governance.
- L&D, HR and communications professionals preparing teams for AI-enabled ways of working.
- Project, programme and product leaders selecting, piloting or scaling Microsoft AI solutions.
- Professionals preparing for Microsoft Exam AB-731: AI Transformation Leader.
Pre-Requisites
To get the most from this course, participants should have:
- Business experience: Exposure to leading adoption or change management in a team or organisation. No coding is required.
- Microsoft familiarity: A general understanding of Microsoft 365 and of what AI can do.
- Microsoft Learn account: A personal Microsoft account (MSA) for Microsoft Learn, which keeps your exam records if you change employer.
- Software access: Microsoft 365 Copilot Chat, which comes with Microsoft 365, so you can try the activities.
- Preparation: Bring one business process from your own team that you think AI could improve.
Course Outline / Curriculum
Module 1: Generative AI Foundations and Business Value
- Types of AI: How generative AI differs from predictive AI and other types of AI.
- Models: Comparing pretrained and fine-tuned models.
- Cost Drivers and ROI: Tokens, consumption costs and calculating return on investment.
- Challenges: Recognising fabrications, reliability issues and bias.
- When Generative AI Adds Value: Identifying use cases for scale and automation.
Module 2: Prompting, Grounding, Data and Secure AI
- Prompt Engineering: Techniques for writing effective, structured prompts.
- Grounding and RAG: Business requirements for grounding and how retrieval-augmented generation works.
- Data Matters: How data type, quality and representativeness affect AI outcomes.
- Machine Learning: When ML adds value, and the machine learning lifecycle.
- Secure AI: Application, data and authentication controls for trusted AI.
Module 3: Microsoft 365 Copilot and the Copilot Family
- Copilot Chat vs. Microsoft 365 Copilot: What each version can do with and without work data.
- Copilot in the Microsoft 365 Apps: Practical use in Teams, Outlook, Word, Excel and PowerPoint.
- Microsoft Graph, Copilot Studio and Agents: Extending Copilot with company knowledge and actions.
- Researcher and Analyst: Choosing the right agent for cited research or data analysis.
- Build, Buy or Extend: A decision framework for AI solutions.
Module 4: Microsoft Foundry and Foundry Tools
- What Is in the Platform: Microsoft Foundry, Azure AI Search, Document Intelligence, Vision, Speech, Language and Content Safety.
- Matching a Model to the Need: Selecting models and services for business requirements.
- Benefits of Foundry: When to build custom AI applications.
Module 5: Responsible AI and Governance
- Why It Matters: The business and reputational case for responsible AI.
- The Six Principles: Applying Microsoft’s responsible AI principles.
- Governance Principles: Risk assessment, controls and human oversight for high-impact decisions.
- The AI Council: Establishing governance structures and accountability.
Module 6: AI Adoption Planning and Licensing
- Adoption Team and Champions: Building a champions programme to drive uptake.
- Common Barriers: Addressing resistance and barriers to change.
- Impacts to Plan For: Data, privacy, security and cost considerations.
- Copilot Licensing: Selecting the right Copilot licensing model.
- Foundry Tools Subscription Models: Pay-as-you-go vs. commitment tiers.
Schedule Dates and Booking
There are currently no scheduled dates.