Course Program Overview
AB-100: Microsoft Certified: Agentic AI Business Solutions Architect
- Duration: 5 Months
- Format: Live Online / Classroom / Blended / Corporate
- Sessions: 5 per week
- Session Length: 01 Hour of each
- Tech Stack: : Microsoft Copilot Studio, Azure OpenAI Service, Microsoft Foundry, Multi-Agent Orchestration (MAO), Semantic Kernel, AutoGen, Agentic Design Patterns.
- Outcome: Expert-level AI Architect Portfolio + Microsoft AB-100 Certification + Global Career Placement.
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Our placement Record
đź“Ś Key Exam Information
Certification Name
Microsoft Certified: Agentic AI Business Solutions Architect (AB-100)
Level
Expert / Solutions Architect
Role Alignment
AI Architect, Enterprise Solution Lead, Automation Strategist
Duration
~100 minutes
Exam Format
Case studies, architectural design tasks, and scenario-based decision making
Number of Questions
40–55
Passing Score
700 / 1000
Languages Available
English + major global languages
🎯 Who Should Take AB-100
- Experienced Solution Architects designing autonomous, multi-agent AI ecosystems for enterprise scale.
- Technical Consultants transitioning from traditional business process automation to agentic-first workflows.
- Enterprise Leaders responsible for integrating Microsoft Copilot and Azure OpenAI into existing business units.
- Advanced AI Engineers seeking to move into strategic architectural roles focusing on Agentic AI governance and ROI.
🧠Exam Domains & Weightage
25-30%
Plan AI-powered business solutions
Identifying business requirements, evaluating ROI, and designing a strategic roadmap for agentic-first digital transformation.
25-30%
Design AI-powered business solutions
Architecting task-specific agents, autonomous workflows, and complex multi-agent orchestration (MAO) systems.
20-25%
Deploy and govern AI solutions
Implementing Application Lifecycle Management (ALM) for agents, securing model environments, and managing AI safety boundaries.
20-25%
Analyze and tune AI solutions
Monitoring agent telemetry, interpreting feedback loops, and fine-tuning model routing for maximum architectural efficiency.
🏆 Benefits of Certification
- Strategic Leadership: Validate your ability to bridge the gap between technical AI models and high-level business outcomes.
- Architectural Authority: Master the design of autonomous systems that don't just "chat" but execute complex business processes.
- Expert-Level Credibility: Earn Microsoft's most advanced AI title for 2026, setting you apart as an elite Solution Architect.
- Global Demand: Secure roles in organizations looking to deploy autonomous AI agents to replace manual enterprise workflows.
🌟 Top 5 Reasons to Choose Adian Soft Solutions for this course
Exclusive Agentic-First Curriculum
While other programs focus on basic chatbots, our AB-100 course is built specifically for the 2026 "Agentic" era. We provide deep-dive modules on multi-agent orchestration (MAO) and autonomous workflows that move beyond simple assistants to self-executing business systems.
High-Stakes Architectural Decision Labs
The AB-100 exam is about architecture, not just coding. Our labs place you in the role of a Lead Architect where you must design governance frameworks, select model routing strategies, and build enterprise-grade agent environments using Microsoft Copilot Studio.
Focus on Business Value & ROI
We teach you how to bridge the gap between technical AI and business leadership. You will learn to calculate the ROI of agentic automation and present complex AI architectural trade-offs to stakeholders—a core skill set required for the AB-100 certification.
Advanced Governance & Safety Modules
In 2026, AI safety is the top priority for enterprises. Our training includes exclusive modules on "Agentic Guardrails," teaching you how to secure autonomous systems against prompt injection and ensure compliance in highly regulated industries.
Expert-Led Certification Blueprint
Our instructors are practicing AI Architects who provide real-world insights into the AB-100 exam. You receive 2026-updated case study simulations, mock exams, and personalized coaching to ensure you master the architectural mindset needed to pass on your first attempt.
Skills You Will Get
You will gain a strong foundation in artificial intelligence by mastering machine learning concepts, computer vision, natural language processing, and conversational AI. Along the way, you’ll learn to work hands‑on with Azure Cognitive Services, Azure Machine Learning Studio, and Bot Service to build deployable solutions. These skills will empower you to design, integrate, and implement real‑world AI applications that align directly with industry needs and certification standards.
Multi-Agent Orchestration (MAO)
Multi-Agent Orchestration (MAO)
15+ Advanced Design Labs
15+ Advanced Design Labs
2 Architect Capstones
2 Architect Capstones
8+ Strategy Case Studies
8+ Strategy Case Studies
Microsoft Foundry Integration
Microsoft Foundry Integration
Responsible Agentic Governance
Responsible Agentic Governance
ROI & Performance Analytics
ROI & Performance Analytics
Computer Vision
Computer Vision
Course Program
(5 Months)
Classroom / Live Online
120+ Hours
This five month expert level program is designed to transform experienced architects into masters of Agentic AI. By extending the roadmap, each domain is explored in greater depth, with additional labs and case studies to ensure mastery. The journey begins with strategic planning, progresses into architectural design, then governance and lifecycle management, followed by performance tuning and ROI analytics, and finally culminates in a comprehensive Capstone Project.
â—Ź Month 1
Exam Coverage: 20–25% Strategic Planning for Agentic Solutions
The first month focuses on the “Architect’s Vision”—learning to identify business processes ripe for agentic transformation. Learners explore how to evaluate technical feasibility versus business ROI, ensuring AI investments align with corporate goals. We cover foundational principles of agentic first design, including task decomposition and the selection of appropriate Large Language Models (LLMs) for specific domains. Participants also master the art of designing phased AI roadmaps that account for cost, scaling, and stakeholder expectations.
Practical Labs:
Perform ROI analysis for autonomous customer support migration, design a high level solution blueprint for a legal tech agent, and create a resource estimation model for global AI deployment.
Case Studies:
Fortune 500 companies transitioning from chatbots to autonomous agentic workflows; failures of poorly planned AI initiatives.
â—Ź Month 2
Exam Coverage: 20–25% Architectural Design & Multi Agent Orchestration
Month two is the technical heart of the program. Learners master the design of individual task agents and the orchestration required for them to work together (MAO). We dive deep into Azure OpenAI Service integration and the use of Semantic Kernel to create intelligent memory and tool calling capabilities. Students design “self correcting” workflows where agents detect errors in their own tasks and re route logic without human intervention.
Practical Labs:
Build a multi agent system where a “Researcher Agent” and a “Writer Agent” collaborate on financial reports; implement human in the loop checkpoints within a supply chain workflow.
Case Studies:
Autonomous logistics engines; BFSI sector multi agent systems handling complex, non linear tasks.
â—Ź Month 3
Exam Coverage: 20–25% Governance & Application Lifecycle Management (ALM)
This month emphasizes governance and lifecycle management. Learners implement robust frameworks to prevent prompt injection and ensure data privacy. We cover ALM specifically for agents, including versioning, environment promotion, and compliance strategies. Students learn how to establish “Agentic Guardrails” and governance centers of excellence.
Practical Labs:
Configure security guardrails in Microsoft Copilot Studio, set up CI/CD pipelines for agents, and perform red team security audits on deployed autonomous systems.
Case Studies:
Governance failures in regulated industries; deployment of Agentic Centers of Excellence in multinational organizations.
â—Ź Month 4
Exam Coverage: 20–25% Performance Tuning, ROI & Analytics
Learners focus on analyzing and tuning agentic solutions. We cover telemetry, feedback loops, and fine tuning model routing for efficiency. Students learn to calculate ROI of agentic automation and present architectural trade offs to stakeholders. This month emphasizes aligning technical design with measurable business outcomes.
Practical Labs:
Implement telemetry dashboards for agent performance, configure cost to value analytics, and optimize routing strategies for multi agent workflows.
Case Studies:
Enterprises tracking ROI of agentic automation in healthcare and global banking; performance tuning in large scale AI deployments.
â—Ź Month 5
Exam Coverage: 20–25% + Consolidation of 100% Expert Consolidation & Capstone Project
The final month integrates all skills into a professional portfolio. Learners complete full length architectural simulations and case study workshops mirroring the AB 100 exam. The Capstone Project requires designing and deploying enterprise grade agentic workflows that demonstrate mastery of planning, design, governance, and ROI analysis.
Practical Labs:
Execute full exam simulations, refine governance frameworks, and deploy multi agent systems with monitoring and safety guardrails.
Case Studies:
Global organizations achieving “Zero Touch” operations through agentic automation.
Capstone Projects:
- Zero Touch Customer Operations Engine – Autonomous workflow for customer support.
- Self Correcting Supply Chain Workflow – Multi agent orchestration for logistics with built in error recovery.
Real Roles. Real Results.
Explore Your Post-Course Career
After completing the course, learners can unlock high-impact roles such as Machine Learning Engineer, Cloud Solutions Architect, Data Scientist, and AI Product Lead—across sectors like technology, BFSI, healthcare, retail, and manufacturing.
Machine Learning Engineer
Designs, trains, and optimizes ML models for prediction, classification, and automation across industries like finance, healthcare, and manufacturing.
Data Scientist
Extracts insights from structured and unstructured data using statistical analysis, visualization, and modeling techniques. Drives decision-making and business intelligence.
AI Solutions Architect
Leads the design and deployment of scalable AI systems using cloud platforms, MLOps pipelines, and enterprise-grade frameworks
Deep Learning Researcher
Specializes in neural networks, CNNs, RNNs, GANs, and transformers. Builds models for image recognition, NLP, and generative tasks.
MLOps Engineer
Implements CI/CD pipelines, containerization, and cloud-native deployment for AI models. Ensures reliability, scalability, and performance monitoring.
Generative AI Developer
Builds intelligent applications using LangChain, Hugging Face, and LLMs. Applies RAG pipelines and transformer models to domains like legal tech and marketing.
Computer Vision Engineer
Develops image and video analysis systems using OpenCV, TensorFlow, and deep learning. Works on facial recognition, object detection, and OCR.
NLP Engineer
Creates language models and conversational AI systems using NLTK, SpaCy, and transformers. Powers chatbots, sentiment analysis, and document summarization.
AI Product Lead
Bridges technical teams and business strategy. Oversees AI product lifecycle—from ideation to deployment—ensuring alignment with market needs and ethical standards.
Frequently Asked Questions
AB-100 Microsoft Certified: Agentic AI Business Solutions Architect
A standard AI Engineer (like AI-102) focuses on implementing individual AI services such as vision or speech. An Agentic AI Architect (AB-100) designs high-level systems where multiple autonomous agents work together to solve complex, multi-step business problems without constant human intervention.
Yes. To earn the "Expert" title, Microsoft requires you to have an active Associate-level certification. Recommended paths include the Azure AI Engineer Associate (AI-102) or specific Microsoft 365/Power Platform developer certifications.
As of 2026, the demand is highest in FinTech, Healthcare, and Global Logistics. These industries are moving toward "Zero-Touch" operations where Agentic AI handles everything from loan processing to supply chain coordination.
Absolutely. Microsoft Copilot Studio is a core component of the AB-100 curriculum. You will learn to build, manage, and publish sophisticated agents directly within the Microsoft ecosystem.
The AB-100 exam is heavy on scenario-based decision-making. We provide exclusive "Architectural War Rooms" where you analyze real-world business failures and redesign them using Agentic AI patterns, mirroring the exact difficulty of the official exam.
Yes, the exam can be taken through Pearson VUE’s online proctoring system or at an authorized testing center. Our team assists you with the full registration process and helps you navigate the 2026 scheduling requirements
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Partnering with Adian Soft Solutions transformed our AI adoption journey. Their training programs gave our team the confidence to deploy advanced ML models in production. The hands-on labs and real-world case studies were game changers.
Priya Sharma, CTO Global Tech Innovators