Applied AI

Applied AI

Microsoft Copilot and Intelligent Agents for Business - 2 days

Practical AI skills for better analysis, automation, decision support, and business productivity.

Artificial intelligence is becoming part of everyday business work rather than remaining a specialist technology confined to data science teams. Microsoft Copilot, generative AI, low-code automation, and AI agents are increasingly being used to help people analyze information, create business content, retrieve knowledge, automate repetitive activities, and support more complex workflows. This creates a practical need for business professionals to understand not only how to use these technologies, but also where they are appropriate, how to structure interactions with them, and how to manage their limitations.

This two-day course provides a focused introduction to the AI capabilities most relevant to modern business environments. It begins with the fundamentals needed by participants who are relatively new to generative AI and progresses into prompt engineering, Microsoft Copilot, Copilot Studio, Power Platform AI, and the design of AI agents. The intention is not to turn participants into AI developers in two days. Instead, the course develops enough practical understanding for participants to use AI effectively, recognize suitable business opportunities, participate in AI-enabled solution design, and communicate intelligently with technical and governance teams.

Particular attention is given to the distinction between using AI as an individual productivity tool and incorporating AI into repeatable business processes. Participants will examine how prompts, organizational knowledge, workflows, tools, and agents fit together, along with the security and governance considerations that become increasingly important as AI moves from personal use into enterprise solutions. Microsoft currently distinguishes lightweight agent creation through Microsoft 365 Agent Builder from the more extensive integration, orchestration, and governance capabilities available through Copilot Studio.

The course is deliberately practical and business-oriented. The instructor has over 30 years of industry experience and will use real industry-demanded content rather than presenting the subject as an academic study of artificial intelligence. Given the limited two-day duration, the course concentrates on useful concepts, capabilities, and decision-making skills rather than attempting exhaustive coverage of every Microsoft AI product or feature.

Learning Outcomes

By the end of the course, participants should be able to:

• Explain generative AI, copilots, and AI agents in practical business terms.
• Identify appropriate and inappropriate business uses of generative AI.
• Use Microsoft Copilot more effectively for common knowledge-work activities.
• Develop structured prompts that produce more relevant and consistent results.
• Recognize limitations such as hallucination, incomplete context, and unreliable output.
• Understand the role of Copilot Studio in building business-focused AI agents.
• Explain how knowledge, instructions, tools, actions, and orchestration contribute to agent behavior.
• Understand how Power Platform capabilities can incorporate generative AI into applications and workflows.
• Identify opportunities for AI-assisted process improvement and automation.
• Recognize fundamental security, privacy, access, compliance, and AI governance considerations.
• Participate more effectively in the planning and evaluation of AI-enabled business solutions.

Prerequisites

• General experience working with business processes or business applications.
• Basic familiarity with Microsoft 365 applications.
• General understanding of workflow and process improvement concepts is beneficial.
• No programming experience is required.
• No previous AI experience is required.
• Previous exposure to Microsoft Copilot or Power Platform is beneficial but not essential.

Training Outline

1. Generative AI Fundamentals for Business
   1. Understanding Generative AI
      1. Large language models
      2. Generative versus traditional AI
      3. AI capabilities and limitations
      4. Hallucination and reliability
      5. Human oversight
   2. AI in the Business Environment
      1. Productivity enhancement
      2. Information analysis
      3. Knowledge retrieval
      4. Decision support
      5. Process automation opportunities
   3. Copilots and AI Agents
      1. AI assistants
      2. Copilots
      3. AI agents
      4. Agentic workflows
      5. Human and AI responsibilities
2. Microsoft Copilot for Business Productivity
   1. Microsoft Copilot Fundamentals
      1. Microsoft 365 Copilot
      2. Copilot Chat
      3. Organizational grounding
      4. Business information handling
      5. Copilot limitations
   2. Business Productivity Applications
      1. Content generation
      2. Information summarization
      3. Research and synthesis
      4. Document analysis
      5. Meeting and communication support
   3. Responsible Copilot Usage
      1. Output validation
      2. Sensitive information
      3. Access permissions
      4. Human review
      5. Appropriate use boundaries
3. Context Engineering
   1. Context Design Fundamentals
      1. Goals and instructions
      2. Context
      3. Constraints
      4. Audience
      5. Output requirements
   2. Improving Prompt Quality
      1. Prompt refinement
      2. Iterative prompting
      3. Structured outputs
      4. Context management
      5. Result evaluation
   3. Business Prompting Techniques
      1. Analysis prompts
      2. Comparison prompts
      3. Extraction prompts
      4. Transformation prompts
      5. Reusable prompt patterns
   4. Prompt Builder
      1. Custom prompts
      2. Prompt testing
      3. Prompt variables
      4. Generative AI actions
      5. Power Platform integration
4. AI Agents with Microsoft Copilot Studio
   1. Copilot Studio Fundamentals
      1. Agent concepts
      2. Agent instructions
      3. Knowledge sources
      4. Topics
      5. Tools and actions
   2. Agent Behavior and Orchestration
      1. Generative orchestration
      2. Tool selection
      3. Multi-step interactions
      4. Business rules
      5. Human intervention
   3. Business Agent Design
      1. Agent purpose and scope
      2. User requirements
      3. Knowledge boundaries
      4. Actions and permissions
      5. Testing and validation
   4. Agent Lifecycle
      1. Building
      2. Testing
      3. Publishing
      4. Monitoring
      5. Continuous improvement
5. Power Platform AI and Business Automation
   1. Power Platform AI Landscape
      1. Power Apps
      2. Power Automate
      3. AI Builder
      4. Copilot Studio
      5. Dataverse concepts
   2. AI-Enabled Automation
      1. Generative AI in workflows
      2. AI-assisted information processing
      3. Workflow actions
      4. Approvals and human intervention
      5. Process automation boundaries
   3. Selecting the Right Approach
      1. Copilot versus automation
      2. Agent versus workflow
      3. AI-assisted versus deterministic processes
      4. Low-code solution considerations
6. AI Governance, Security and Responsible Adoption
   1. Enterprise AI Governance
      1. AI usage policies
      2. Roles and responsibilities
      3. Environment governance
      4. Agent governance
      5. Lifecycle controls
   2. Data and Security Considerations
      1. Authentication
      2. Authorization
      3. Data access
      4. Connector governance
      5. Sensitive information
   3. Responsible AI
      1. Accuracy and reliability
      2. Transparency
      3. Human accountability
      4. Risk assessment
      5. Monitoring and review
   4. Moving from Experimentation to Business Adoption
      1. Use-case prioritization
      2. Business value assessment
      3. Risk versus benefit
      4. Adoption considerations
      5. Continuous governance

Disclaimer

This course outline is intended as a structured guideline for the delivery of the training and represents the anticipated scope based on the stated duration and learning objectives. The trainer reserves the right to amend, reorder, expand, reduce, or substitute individual topics where reasonably necessary to accommodate participant experience, available time, changes in technology, operational considerations, or instructional priorities, without prior notice.