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AB-100T00: Architecting agentic AI business solutions Training

AB-100T00 is for architects and technical leaders who need to design AI powered business solutions using agents, copilots, and generative AI on Microsoft platforms. It's about real world architecture, not abstract theory.

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| AB-100T00: Architecting agentic AI business soluti

Course Overview

This course teaches you to design AI powered business solutions using agents, copilots, and generative AI on Microsoft platforms. It covers real world architecture decisions, including trade offs, governance, and lifecycle management. You'll learn how to align AI with business goals, evaluate ROI, and build solutions that are both scalable and secure. It's designed for people who have to make architecture decisions that stick.

Mode of Training

🏫 Classroom 💻 Live Online 🧪 Blended 👨‍👩‍👧‍👦 Private Group

Upcoming Schedules

Start Date Time Duration Mode Price
Apr 28, 2026 9:00 am - 5:00 pm 3 Day Online
$1595
May 08, 2026 9:00 am - 5:00 pm 3 Day Online
$1595
May 28, 2026 9:00 am - 5:00 pm 3 Day Online
$1595
Jun 11, 2026 9:00 am - 5:00 pm 3 Day Online
$1595
Jun 30, 2026 9:00 am - 5:00 pm 3 Day Online
$1595
+ View more schedules

What you will learn

  • Design end-to-end agentic AI solutions aligned with business goals
  • Analyze requirements and identify appropriate AI, Copilot, and agent use cases
  • Evaluate cost, ROI, and build vs. buy decisions for AI solutions
  • Architect scalable and extensible solutions using Microsoft Copilot and Power Platform
  • Implement robust testing strategies and validation frameworks for AI systems
  • Apply responsible AI principles including security, governance, and compliance

Who Should Attend This Course?

  • Automation Architect
  • Technical Architect
  • System Architect
  • Dynamics 365 Finance & Operations App Developer
  • Dynamics Functional Consultant
  • Dynamics Architect
  • Business Managers
  • Power Platform App Maker

Prerequisites

  • Basic understanding of AI concepts
  • Familiarity with business process analysis
  • Knowledge of Microsoft tools and platforms

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📘 AB-100T00: Architecting agentic AI business solutions Outline

Introduction to Agentic AI Business Solutions

  • Introduction
  • Drive AI transformation with architect strategies
  • Explore Microsoft AI technologies for business
  • Identify Microsoft AI technologies for business solutions
  • Identify out-of-box Microsoft AI agent resources for business solutions
  • Identify out-of-box Microsoft AI agents for business

Analyze Requirements for AI-Powered Business Solutions

  • Introduction
  • Assess the use of agents in task automation, data analytics, and decision-making
  • Review data for grounding accuracy, relevance, timeliness, cleanliness, and availability
  • Organize business solution data for AI systems

Evaluate Costs and Benefits of AI Solutions

  • Introduction
  • Evaluate ROI criteria for AI-powered solutions
  • Create ROI analysis for a proposed AI solution
  • Analyze whether to build, buy, or extend AI components
  • Implement a model router to intelligently route requests to the most suitable model

Manage Testing AI-Powered Business Solutions

  • Introduction
  • Recommend process metrics for testing AI agents
  • Create validation criteria for custom AI models
  • Validate effective Copilot prompt best practices
  • Design end-to-end test scenarios for AI solutions using multiple Dynamics 365 apps
  • Build a strategy for creating test cases using Copilot

Design Extensibility of AI Solutions

  • Introduction
  • Design AI solutions with custom models in Microsoft Foundry
  • Design agents in Microsoft 365 Copilot
  • Design extensible agents in Microsoft Copilot Studio
  • Design extensible agents using MCP in Copilot Studio
  • Design agents to automate tasks in apps and websites with Computer Use in Copilot Studio
  • Design agent behaviors in Copilot Studio
  • Optimize solution design for agents in Microsoft 365

Design Responsible AI: Security, Governance, Risk Management, and Compliance

  • Introduction
  • Design security agents for Microsoft clouds
  • Design governance models for AI agents
  • Design model security for responsible AI
  • Analyze AI vulnerabilities and mitigations for prompt manipulation
  • Review solution adherence to Responsible AI principles
  • Validate data residency and movement compliance
  • Design access controls for grounding data and model tuning
  • Design audit trails for changes to models and data

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