AB-100 : Agentic AI enterprise solution architecture

A B1 level of English is recommended. You can find the proficiency levels at this link: Language proficiency level classification.

Introducing Agentic AI Enterprise Solutions

• Explain the architect’s role in driving AI adoption and transformation.
• Identify the key responsibilities of an AI architect in business contexts.
• Learn how architects align AI solutions with organizational goals.
• Apply best practices for scaling AI in enterprise environments.
• Identify key Microsoft AI services and tools.
• Explore Microsoft Copilot solutions and their business value.
• Learn how generative AI is unlocking productivity in enterprise environments.
• Identify the Microsoft AI OOB agent resources available for line-of-business solutions.

Analyze requirements for AI-powered business solutions

• Explain how AI agents support task automation, data analytics, and decision-making.
• Describe the role of Microsoft Copilot and generative AI in improving productivity.
• Evaluate scenarios where AI agents add measurable value to enterprise environments.
• Assess the quality of baseline data based on accuracy, relevance, timeliness, cleanliness, and availability.
• Organize enterprise solution data for AI readiness and large-scale consumption.

Design a holistic AI strategy for business solutions

• Match the AI adoption phases of the Cloud Adoption Framework (CAF) with the AI agent lifecycle.
• Design an enterprise-ready operating model for AI agents.
• Select and use Microsoft platforms for AI solutions.
• Support the transition of AI workloads from POC to production.

Evaluate the costs and benefits of AI solutions

• Define ROI criteria and evaluate the total cost of ownership (TCO) for AI solutions.
• Create a comprehensive ROI analysis for AI-optimized business processes.
• Analyze and decide whether to build, purchase, or extend AI components.
• Implement model routing strategies to optimize AI performance and costs.

Design AI agents for business solutions

• Apply the principles of responsible AI to the design of the AI agent.
• Configure business terms and customize Copilot in Dynamics 365.
• Design custom connectors and integrate AI agents with Dynamics 265 Contact Center.
• Create autonomous, task-oriented agents using Copilot Studio.
• Implement guest-controlled chatbots with responsive responses.

Design the scalability of AI solutions

• Build scalable and secure AI solutions using Microsoft platforms.
• Leverage custom templates in Microsoft Foundry.
• Design and operationalize agents in Microsoft 365 Copilot.
• Extend agent functionality by using Copilot Studio and Model Context Protocol (MCP).
• Apply governance and lifecycle management for AI solutions.

Orchestrate the configuration of predefined agents and applications

• Orchestrate Copilot AI capabilities and agents across Dynamics 365 and Microsoft 365 apps.
• Design secure, compliant, and extensible AI solutions.
• Configure and implement pre-built Copilot agents for finance, supply chain, sales, and service scenarios.
• Apply best practices for responsible measurement of AI, workflow integration, and success.

Monitor, analyze, and tune AI agents

• Establish monitoring frameworks for AI agents.
• Apply industry tools and processes for observability.
• Analyze backlogs and user feedback to gain actionable insights.
• Apply AI-based diagnostic and tuning methods.
• Monitor performance and metrics to optimize agent workflows.

Manage AI-based business solution testing

• Design structured testing processes for AI agents, custom models, and multi-application scenarios.
• Define measurable validation criteria for performance, security, and compliance.
• Implement scalable testing strategies using Copilot to ensure consistency and coverage.
• Ensure that AI solutions align with business goals and remain reliable throughout their lifecycle.

Design an ALM process for AI-powered business solutions

• Design ALM processes for AI components such as datasets, prompts, and models.
• Establish governance, security, and oversight across environments.
• Ensure consistent and compliant AI behavior from development to production.

Design responsible AI security, governance, risk management, and compliance

• Design AI systems that balance innovation with accountability.
• Enforce identity, access control, and data governance to secure AI agents.
• Implement observability and threat protection for AI solutions.
• Translating compliance requirements into technical controls.
• Mitigate vulnerabilities across prompts, templates, and workflows.

In addition, to ensure rigorous tracking, each participant signs an attendance sheet for each half-day session.

Finally, we offer flexibility in delivering this training, which can be conducted either in-person or remotely. It can also be customized to meet your company’s specific needs upon request.

To reach us, several public transport options are available:

• Take metro line 9 and get off at Pont de Sèvres,
• Take metro line 10 to Boulogne Jean Jaurès,
• Or take tram line T2 to Brimborion.

This training paves the way to the Microsoft certification “AI Transformation Leader.” We recommend registering for the exam approximately one month after completing the training. The course materials provided during the training will help you prepare effectively for the certification.

Certification registration is done directly on Microsoft’s website. If you would like to purchase a certification voucher from us or receive support with the process, please contact us.