About this class

This course teaches leaders and practitioners how to plan, design, and prototype task-seeking AI assistants that use tools, memory, and multi-step workflows. Students will learn to map business processes to agentic workflows, compare platform options including Microsoft Copilot Studio, Power Automate, and Amazon Bedrock Agents, and implement safety controls such as tool scopes, confirmation gates, and audit trails. The course emphasizes practical implementation patterns and organizational adoption strategies.

Participants will gain hands-on experience designing agent architectures (planners, routers, reviewers, tool-callers), configuring multi-step workflows with human-in-the-loop controls, implementing data permissions and security, building reliability patterns with fallbacks and retries, and creating adoption plans with change management strategies. Through progressive labs and a capstone project, students will develop a complete agent proof-of-concept ready for organizational review.

Who should attend?

This course is designed for leaders designing AI-assisted processes across operations, customer experience, finance, HR, claims, and related business domains. Product and operations leads, solution owners and architects, business process analysts, and technical leads implementing agentic AI solutions will benefit from this practical, implementation-focused curriculum.

What you'll be able to do

In this course, you will learn how to

M ap business processes to agentic workflows using plan act check
report patterns .
D esign agent
focused curriculum .
including planners , routers , reviewers , and tool -
calling agents .
E valuate and select appropriate tooling options : C opilot S tudio actions , P ower
A utomate, B edrock A gents , and low-
code patterns .
I mplement safety controls including tool scopes , confirmation gates , least
privilege access, and audit trails .
B uild reliability patterns with fallbacks , timeouts ,
retries , and handoff procedures .
C reate organizational adoption plans with rollout strategies , enablement
materials , and success metrics .
T opics
A gent design patterns : planner , router , reviewer , and tool - caller architectures
G oal definition, tool selection , guardrail implementation, and success metrics
M icrosoft C opilot S tudio actions and custom copilot development
P ower A utomate flow orchestration and integration patterns
A mazon B edrock A gents configuration and deployment
D ata permissions , least privilege access, and sensitive data masking
C onfirmation gates and human- in - the- loop workflow patterns
A udit logging, compliance tracking, and governance controls
R eliability engineering: fallbacks , timeouts , retries , and graceful degradation
I mpact measurement , change management , and organizational adoption
strategies
P rerequisites
Prior to attending, students should have:
C omfort with business process mapping and workflow design
U nderstanding of organizational processes and approval workflows
F amiliarity with enterprise software systems and integrations ( helpful but not
required)
M odern web browser with internet access
A ccess to M icrosoft C opilot S tudio and P ower A utomate , or A mazon B edrock
A gents ( instructor demos available if access is limited )
C ourse Outline
Module 1: Agent Architecture Patterns
Introduction to Agentic AI Systems
o Agent vs. traditional automation: autonomy, reasoning, and tool use
o Core agent patterns: planner, router, reviewer, and tool - caller
Designing Your First Agent
o Goal definition and success criteria
o Tool inventory and capability mapping
o Guardrail design and safety boundaries
Hands - On Lab 1: Sketch Your Agent Design
o D efine agent goals and success metrics
o Identify required tools and data sources
o Design guardrails and safety controls
o Create agent design canvas documentation
Module 2: Platform Tooling Options
Microsoft Copilot Studio and Actions
o Custom copilot creation and configuration
o Action design and connector integration
o Conversation flow and topic management
Power Automate Flow Orchestration
o Multi- step workflow design and triggers
o Conditional logic and branching patterns
o Error handling and retry mechanisms
Amazon Bed rock Agents
o Agent configuration and foundation model selection
o Action group definition and API integration
o Knowledge base grounding and retrieval
Hands - On Lab 2: Configure a Multi - Step Flow with Human- in - the - Loop
o Build agent workflow with approval steps
o Implement confirmation gates and user notifications
o Configure timeout handling and escalation paths
o Test complete workflow end- to - end
Module 3: Data Security and Permissions
Least Privilege Access Design
o Role - based access control (RBAC) for agent operations
o Data source permissions and connection security
o API key management and credential vaulting
Sensitive Data Protection
o PII detection and masking strategies
o Data classification and handling policies
o Compliance considerations (GDPR, HIPAA, etc.)
Audit and Compliance Controls
o Logging agent actions and decisions
o Audit trail design and retention policies
o Compliance reporting and governance integration
Module 4: Reliability and Error Handling
Failure Modes and Mitigation
o Common failure patterns in agentic systems
o Timeout configuration and handling
o Retry logic with exponential backoff
Fallback Strategies
o Graceful degradation patterns
o Human handoff triggers and escalation
o Alternative tool selection and routing
Hands - On Lab 3: Add Reliability Controls to Your Agent
o Implement confirmation gates for high- risk actions
o Configure audit logging for compliance
o Add timeout handling and retry logic
o Test failure scenarios and recovery
Module 5: Measuring Impact and Driving Adoption
Success Me trics and KPIs
o Task completion rates and accuracy
o Time savings and efficiency gains
o User satisfaction and adoption metrics
o Cost analysis and ROI calculation
Change Management and Rollout
o Pilot program design and participant selection
o Training and enablement strategies
o Feedback collection and iteration
o Scaling from pilot to production
Hands - On Lab 4 - Capstone: Agent POC Plan and Demo
o Create 2 - page agent proof - of - concept proposal
o Develop demo script and walkthrough
o Design 90- day rollout plan with milestones
o Prepare stakeholder presentation materials
o Present POC and adoption strategy

Course outline

Agentic AI & Workflow Orchestration Course ISI - 1 619 2 Days Instructor - led, Hands on Course Description - seeking AI assistants that use tools, memory, and multi - step workflows. Students will learn to map business processes to agentic workflows, compare platform options including Microsoft Copilot Studio, Power Automate, and Amazon Bedrock Agents, and implement safety controls such as tool scopes, confirmation gates, and audit trails. The course s. Participants will gain hands - on experience designing agent architectures (planners, routers, reviewers, tool - callers), configuring multi - step workflows with human - in - the - loop controls, implementing data permissions and security, building reliability patter ns with fallbacks and retries, and creating adoption plans with change management strategies. Who Should Attend? T his course is designed for leaders designing AI - assisted processes across operations, customer experience, finance, HR, claims, and related business domains. Product and operations leads, solution owners and architects, business process analysts, and technical leads implementing agentic AI solutions will benefit from this practical, proof - of - concept ready for organizational review. Course Objectives In this course, you will learn how to: M ap business processes to agentic workflows using plan act check report patterns . D esign agent

focused curriculum .

including planners , routers , reviewers , and tool - calling agents . E valuate and select appropriate tooling options : C opilot S tudio actions , P ower A utomate, B edrock A gents , and low- code patterns . I mplement safety controls including tool scopes , confirmation gates , least privilege access, and audit trails . B uild reliability patterns with fallbacks , timeouts , retries , and handoff procedures . C reate organizational adoption plans with rollout strategies , enablement materials , and success metrics . T opics A gent design patterns : planner , router , reviewer , and tool - caller architectures G oal definition, tool selection , guardrail implementation, and success metrics M icrosoft C opilot S tudio actions and custom copilot development P ower A utomate flow orchestration and integration patterns A mazon B edrock A gents configuration and deployment D ata permissions , least privilege access, and sensitive data masking C onfirmation gates and human- in - the- loop workflow patterns A udit logging, compliance tracking, and governance controls R eliability engineering: fallbacks , timeouts , retries , and graceful degradation I mpact measurement , change management , and organizational adoption strategies P rerequisites Prior to attending, students should have: C omfort with business process mapping and workflow design U nderstanding of organizational processes and approval workflows F amiliarity with enterprise software systems and integrations ( helpful but not required) M odern web browser with internet access A ccess to M icrosoft C opilot S tudio and P ower A utomate , or A mazon B edrock A gents ( instructor demos available if access is limited ) C ourse Outline Module 1: Agent Architecture Patterns Introduction to Agentic AI Systems o Agent vs. traditional automation: autonomy, reasoning, and tool use o Core agent patterns: planner, router, reviewer, and tool - caller Designing Your First Agent o Goal definition and success criteria o Tool inventory and capability mapping o Guardrail design and safety boundaries Hands - On Lab 1: Sketch Your Agent Design o D efine agent goals and success metrics o Identify required tools and data sources o Design guardrails and safety controls o Create agent design canvas documentation Module 2: Platform Tooling Options Microsoft Copilot Studio and Actions o Custom copilot creation and configuration o Action design and connector integration o Conversation flow and topic management Power Automate Flow Orchestration o Multi- step workflow design and triggers o Conditional logic and branching patterns o Error handling and retry mechanisms Amazon Bed rock Agents o Agent configuration and foundation model selection o Action group definition and API integration o Knowledge base grounding and retrieval Hands - On Lab 2: Configure a Multi - Step Flow with Human- in - the - Loop o Build agent workflow with approval steps o Implement confirmation gates and user notifications o Configure timeout handling and escalation paths o Test complete workflow end- to - end Module 3: Data Security and Permissions Least Privilege Access Design o Role - based access control (RBAC) for agent operations o Data source permissions and connection security o API key management and credential vaulting Sensitive Data Protection o PII detection and masking strategies o Data classification and handling policies o Compliance considerations (GDPR, HIPAA, etc.) Audit and Compliance Controls o Logging agent actions and decisions o Audit trail design and retention policies o Compliance reporting and governance integration Module 4: Reliability and Error Handling Failure Modes and Mitigation o Common failure patterns in agentic systems o Timeout configuration and handling o Retry logic with exponential backoff Fallback Strategies o Graceful degradation patterns o Human handoff triggers and escalation o Alternative tool selection and routing Hands - On Lab 3: Add Reliability Controls to Your Agent o Implement confirmation gates for high- risk actions o Configure audit logging for compliance o Add timeout handling and retry logic o Test failure scenarios and recovery Module 5: Measuring Impact and Driving Adoption Success Me trics and KPIs o Task completion rates and accuracy o Time savings and efficiency gains o User satisfaction and adoption metrics o Cost analysis and ROI calculation Change Management and Rollout o Pilot program design and participant selection o Training and enablement strategies o Feedback collection and iteration o Scaling from pilot to production Hands - On Lab 4 - Capstone: Agent POC Plan and Demo o Create 2 - page agent proof - of - concept proposal o Develop demo script and walkthrough o Design 90- day rollout plan with milestones o Prepare stakeholder presentation materials o Present POC and adoption strategy

Before you attend

Prior to attending this course, students should have:

Comfort with business process mapping and workflow design
Understanding of organizational processes and approval workflows
Familiarity with enterprise software systems and integrations (helpful but not required)
Modern web browser with internet access
Access to Microsoft Copilot Studio and Power Automate, or Amazon Bedrock Agents (instructor demos available if access is limited)

Who this is for

T his course is designed for leaders designing AI - assisted processes across operations,
customer experience, finance, HR, claims, and related business domains. Product and
operations leads, solution owners and architects, business process analysts, and
technical leads implementing agentic AI solutions will benefit from this practical,
proof - of - concept ready for organizational review.

Run this for a team

Private cohorts run on your dates, at your site or online, with the labs pointed at your environment. Above about four people it usually costs less than buying seats.

Agentic AI & Workflow Orchestration ISI-1619

About this class

Who should attend?

What you'll be able to do

Course outline

Before you attend

Who this is for

Run this for a team

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