AB-100T00-A: Architecting agentic AI business solutions

Course Overview

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 agents—powered by large language models, tools, workflows, and orchestration frameworks—can 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.

Flexible Training Options to
Meet Your Needs

We know the importance of flexibility in the success of learning and professional development. This is the reason CounselTrain provides a variety of delivery options for all IT training offered in the UAE to ensure access and convenience for each learner.

Select the method that best suits your needs.

Online Instructor-Led Training

Learn from the comfort of your workplace or at home through live virtual sessions led by expert trainers.

Classroom Training

Participate in interactive, face-to-face training in our top 5-star training facilities in Dubai

Onsite Training

Learn a customized curriculum in your workplace to ensure the most impact and team participation.

Overseas Training

Participate in our international training sessions and improve your abilities with world-class instructors.

Target Audiance

This course is ideal for solution architects, AI engineers, IT leaders, business analysts, consultants, and professionals involved in designing or managing AI-driven business solutions.

Schedule Dates

09 March 2026 - 11 March 2026

AB-100T00-A: Architecting agentic AI business solutions

15 June 2026 - 17 June 2026

AB-100T00-A: Architecting agentic AI business solutions

21 September 2026 - 23 September 2026

AB-100T00-A: Architecting agentic AI business solutions

21 December 2026 - 23 December 2026

AB-100T00-A: Architecting agentic AI business solutions

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

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 agents
Propose Microsoft AI services 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
Design extensibility of AI solutions
Design AI solutions by using custom models in Azure AI 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
Orchestrate configuration for prebuilt agents and apps
Orchestrate AI in Dynamics 365 apps for finance and supply chain
Orchestrate AI in Dynamics 365 apps for customer experience and 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

Recommend the process and tools required 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
Manage the testing of AI-powered business solutions
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
Design the ALM process for AI-powered business solutions
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 Azure AI services 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
Design responsible AI, security, governance, risk management, and compliance
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

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.

Agentic AI can be applied to process automation, customer support, decision intelligence, operations optimisation, data analysis, workflow orchestration, and enterprise knowledge management.

Yes. The course focuses heavily on real-world business scenarios and practical architecture patterns used in modern enterprises.

The course includes guidance on responsible AI, data privacy, compliance, risk management, and governance frameworks critical for enterprise AI adoption.

Graduates will be better positioned for roles such as AI Solution Architect, Enterprise Architect, AI Consultant, Automation Lead, or Digital Transformation Manager.

AB-100T00-A: Architecting agentic AI business solutions

Course Overview

Course Objectives & Learning Outcomes: