AB-100T00-A: Architecting agentic AI business solutions
AB-100T00-A: Architecting Agentic AI Business Solutions is an advanced, industry-focused course designed for professionals who want to design, architect, and implement agentic AI systems that operate autonomously, collaborate intelligently, and deliver measurable business value.
The course explores how modern AI agentsâpowered by large language models, tools, workflows, and orchestration frameworksâcan be applied to real-world business scenarios such as automation, decision support, customer experience, operations, and enterprise transformation. Learners will gain hands-on exposure to architecting scalable, secure, and responsible agentic AI solutions aligned with organisational goals.
This course bridges the gap between AI theory and enterprise implementation, equipping participants with the skills needed to lead AI-driven innovation initiatives.
Course Objectives & Learning Outcomes:
- Understand the core concepts and architecture of agentic AI systems
- Design AI agents that can reason, plan, act, and collaborate autonomously
- Architect end-to-end agentic AI solutions aligned with business requirements
- Integrate AI agents with enterprise systems, APIs, and data sources
- Apply governance, security, and ethical principles to agentic AI deployments
- Evaluate use cases where agentic AI delivers measurable ROI
- Design scalable, maintainable, and production-ready AI architectures
- Communicate AI solution designs effectively to technical and non-technical stakeholders
As an AI-first solution architect, you lead the transformation of enterprise operations by envisioning and implementing AI-powered architecture. With a focus on making the most of the full spectrum of Microsoft AI apps and services, along with business application tools, you drive innovation and help to ensure the delivery of impactful AI-powered solutions.
Who Should Attend
Schedule Dates
Course Content
- Assess the use of agents in task automation, data analytics, and decision-making
- Review data for grounding, including accuracy, relevance, timeliness, cleanliness, and availability
- Organize business solution data to be available for other AI systems
- Design overall AI strategy for business solutions
- Implement the AI adoption process from the Cloud Adoption Framework for Azure
- Design the strategy for building AI and agents in business solutions
- Design a multi-agent solution by using platforms such as Microsoft 365 Copilot, Copilot Studio, and Azure AI Foundry
- Develop the use cases for prebuilt agents in the solution
- Define the solution rules and constraints when building AI components with Copilot Studio, Azure AI services, and Azure AI Foundry
- 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 for the solution
- Provide prompt engineering guidelines and techniques for AI-powered business solutions
- Include the elements of the Microsoft AI Center of Excellence
- Design AI solutions that use multiple Dynamics 365 apps
- Evaluate the costs and benefits of an AI-powered business solution
- Select ROI criteria for AI-powered business solutions, including the total cost of ownership
- 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
FAQs
Agentic AI refers to AI systems composed of autonomous agents that can reason, make decisions, take actions, and collaborate with other agents or tools. Unlike traditional AI models that respond to single prompts, agentic AI systems operate continuously to achieve defined goals.
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