Course Overview of AB-100: Architecting agentic AI business solutions:

Architecting agentic AI business solutions is an advanced course for architects, senior consultants, and technical leaders responsible for planning, designing, and governing AI-powered enterprise solutions built on Microsoft platforms.  

This course serves as a foundational, real-world, and architectural preparation step that builds the design judgment, strategic reasoning, and end-to-end understanding learners need before pursuing the AB‑100 exam or implementing agentic AI solutions at scale.  

Learners will explore how to architect AI-powered business solutions that use agents, copilots, and generative AI to automate tasks, improve decision-making, and enhance employee and customer experiences. Emphasis is placed on architecture, trade-offs, governance, cost/benefit analysis, and lifecycle management, rather than step-by-step configuration. 

After completing AB-100: Architecting agentic AI business solutions, participants will be able to

  • Design end-to-end architectures for agentic AI and generative AI solutions
  • Evaluate and select appropriate AI models based on business requirements
  • Implement copilots and intelligent agents for enterprise use cases
  • Apply governance, security, and responsible AI principles in solution design
  • Plan and integrate data sources for AI solutions, including RAG-based systems
  • Analyze cost, performance, and scalability trade-offs in AI architectures
  • Design enterprise-grade AI solutions using Microsoft AI services and platforms
  • Establish monitoring, evaluation, and lifecycle management strategies for AI systems
  • Align AI solutions with business goals through structured use case prioritization
  • Apply best practices for deploying and managing AI solutions in production environments

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Key Features of AB-100: Architecting agentic AI business solutions:

  • Focus on architecting agentic AI solutions using copilots, agents, and generative AI

  • Emphasis on enterprise architecture patterns, design trade-offs, and scalability  

  • Covers governance, security, and responsible AI practices for real-world deployments  

  • Explores cost-benefit analysis and ROI-driven AI solution design  

  • Hands-on understanding of integrating AI into business applications and workflows  

  • Strong focus on lifecycle management, monitoring, and optimization of AI systems

  • Designed for solution architects and technical leaders with real-world use cases  

  • Aligns with Microsoft AI ecosystem (Copilot, Power Platform, Dynamics, Azure AI) for enterprise adoption  

Who should Attend AB-100: Architecting agentic AI business solutions?

  • Solution Architects and Technical Leads designing enterprise AI solutions
  • AI/ML Engineers and Developers transitioning into architecture roles
  • IT Decision Makers and Technology Consultants driving AI adoption
  • Professionals involved in digital transformation and AI strategy initiatives

Prerequisites of AB-100: Architecting agentic AI business solutions:

  • Familiarity with Microsoft business applications such as Dynamics 365, Microsoft 365, or Power Platform
  • Understanding of cloud computing concepts and services (especially Azure fundamentals)
  • Basic knowledge of solution architecture principles and design patterns
  • Experience working with enterprise IT systems or business applications
  • Awareness of AI/ML and generative AI concepts (agents, copilots, LLMs)
  • Understanding of data concepts and integration in enterprise solutions
  • Exposure to governance, security, and compliance fundamentals in IT systems
  • Prior experience in designing or contributing to technology solutions is recommended

    • Why choose CloudThat as your training partner for AB-100?

    • We provide:  Certified trainers with enterprise AI experience   
    • Hands-on labs aligned with real-world scenarios   
    • Industry-focused curriculum   
    • Continuous support and mentorship   
    • Proven success in Microsoft certifications  

    Course Outline of AB-100: Architecting agentic AI business solutions Download Course Outline

    • Introduction
    • Role of the Architect in AI Transformation for Businesses
    • Overview of Microsoft AI Technologies
    • Identify Out-of-the-Box (OOB) Microsoft AI Agent Resources

    • Introduction
    • Assess the Use of Agents in Task Automation, Data Analytics, and Decision-Making
    • Review Data for Grounding (Accuracy, Relevance, Timeliness, Cleanliness, Availability)
    • Organize Business Solution Data to Be Available for Other AI Systems

    • Introduction
    • Implement the AI Adoption Process from the Cloud Adoption Framework for Azure
    • Design the Strategy for Building AI Agents in Business Solutions
    • Design a Multi-Agent Solution
    • Develop the Use Cases for Prebuilt Agents in the Solution
    • Define the solution rules and constraints when building AI components (with Copilot Studio, Microsoft Foundry, and Foundry Tools)
    • Determine the use of generative AI and knowledge sources in agents built with Copilot Studio
    • Determine When to Build Custom Agents or Extend Microsoft 365 Copilot
    • Determine When Custom AI Models Should Be Created
    • Provide guidelines for creating a prompt library
    • Develop the Use Cases for Customized Small Language Models
    • Prompt Engineering for AI-Powered Business Solutions
    • Identify Key Business User Roles for AI Workloads

    • Introduction
    • Select ROI Criteria for AI-Powered Business Solutions Including Total Cost of Ownership (TCO)
    • Create an ROI Analysis for the Proposed AI Solution for a Business Process
    • Analyze Whether to Build, Buy, or Extend AI Components for Business Solutions
    • Implement a model router to intelligently route requests to the most suitable model

    • Introduction
    • Define the Core Tenets of Microsoft’s Responsible AI Guidelines for AI Business Solutions
    • Design Business Terms for Copilot in Dynamics 365 Apps for Customer Experience and Service
    • Design Customizations of Copilot in Dynamics 365 Apps for Customer Experience and Service
    • Design Connectors for Copilot in Dynamics 365 Sales
    • Design Agents for Integration with Dynamics 365 Contact Center Channels
    • Design Task Agents
    • Design Autonomous Agents
    • Design prompt and Response Agent
    • Propose Foundry Tools for a Given Requirement
    • Propose Code First Generative Pages and the Use of an Agent Feed for Apps
    • Design Topics for Copilot Studio, Including Fallback
    • Design data processing for AI models and grounding
    • Design a Business Process to Include AI Components in a Power Apps Canvas App
    • Apply the Microsoft Power Platform Well-Architected Framework to Intelligent Application Workloads
    • Determine When to Use Standard Natural Language Processing, Azure Conversational Language Understanding, or Generative AI Orchestration in Copilot Studio
    • Design Agents and Agent Flows with Copilot Studio
    • Design Prompt Actions in Copilot Studio
    • Define Success Criteria and Adoption Goals for AI Business Solutions

    • Introduction
    • Design AI solutions by using custom models in Microsoft Foundry
    • Design agents in Microsoft 365 Copilot
    • Design agent extensibility in Copilot Studio
    • Design agent extensibility with Model Context Protocol in Copilot Studio
    • Design Agents to automate tasks in apps and websites by using Computer Use in Copilot Studio
    • Design agent behaviors in Copilot Studio, including reasoning and voice mode
    • Optimize solution design by using agents in Microsoft 365, including Teams and SharePoint

    • Introduction
    • Orchestrate AI features in Dynamics 365 apps for finance and supply chain
    • Design AI solutions in Dynamics 365 apps for customer experience & service
    • Propose Microsoft 365 Agents for Business Scenarios
    • Orchestrate the Configuration of Microsoft 365 Copilot for Sales and Microsoft 365 Copilot for Service
    • Propose Microsoft Power Platform AI features, including AI Hub
    • Design interoperability of the finance and operations agent chats to use additional knowledge sources
    • Recommend the process of adding knowledge sources to in app help and guidance for Dynamics 365 Finance or Dynamics 365 Supply Chain Management apps

    • Introduction
    • Recommend the Process and Tools for Monitoring Agents
    • Analyze backlog and user feedback of AI and agent usage
    • Apply AI Based Tools to Analyze and Identify Issues and Perform Tuning
    • Monitor agent performance and metrics
    • Interpret telemetry data for performance and model tuning

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

    • Introduction
    • Design the ALM process for data used in AI models and agents
    • Design the ALM process for Copilot Studio agents, connectors, and actions
    • Design the ALM process for Microsoft Foundry agents
    • Design the ALM process for custom AI models
    • Design the ALM process for AI in Dynamics 365 apps for finance and supply chain
    • Design the ALM process for AI in Dynamics 365 apps for customer experience and service

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

    Certification Details of AB-100: Architecting agentic AI business solutions:

    • This course aligns with the Microsoft Certified: Agentic AI Business Solutions Architect certification, which validates advanced skills in designing enterprise-grade AI solutions using agentic and generative AI technologies.
    • To earn the certification, candidates must pass the AB-100 exam and may need to hold a relevant Microsoft associate-level certification as a prerequisite, depending on eligibility requirements.
    • The certification focuses on key competencies such as planning, designing, and deploying AI-powered business solutions, with emphasis on architecture, governance, and real-world implementation scenarios.
    • It is categorized as an advanced-level certification intended for solution architects and experienced professionals working with Microsoft AI ecosystem, including Copilot, Power Platform, and Azure AI services.
    • The certification requires annual renewal (typically every 12 months), ensuring professionals stay updated with evolving AI technologies, architecture patterns, and enterprise best practices.

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    Course ID: 28257

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    FAQs of AB-100: Architecting agentic AI business solutions

    This course focuses on designing and architecting agentic AI business solutions using copilots, agents, and generative AI on Microsoft platforms. 

    No, it is designed for experienced professionals with knowledge of cloud, AI concepts, and solution architecture fundamentals.

    It aligns with exam concepts but is not a direct exam preparation course; it focuses on architectural thinking and real-world application.

    You will learn AI architecture design, agent-based systems, copilots, governance, cost optimization, and lifecycle management of AI solutions. 

    Not mandatory; the course emphasizes architecture, design decisions, and enterprise implementation, not coding-heavy tasks.

    Roles such as AI Solution Architect, Technical Consultant, AI Strategy Lead, and Enterprise Architect.

    AI Solution Architects typically earn high salaries ranging from ₹25–50 LPA+ in India (and higher globally) depending on experience and organization.

    The course covers Microsoft AI ecosystem tools, including Copilot, Power Platform, Dynamics 365, and Azure AI services.

    It is typically a 3-day instructor-led course with a focus on architectural concepts and real-world scenarios.

    Unlike development-focused courses, this course emphasizes enterprise architecture, decision-making, governance, and business alignment for AI solutions.

    Enquire Now