Agentic AI for Business Automation: Use Cases & Integration Training Course
Agentic AI for Business Automation is a hands-on course designed to teach participants how to design, integrate, and scale AI-driven agents for real-world business processes. The course focuses on mapping automation opportunities, integrating tools, and building practical use cases across customer service, supply chain, and marketing workflows.
This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to implement AI-powered automation using no-code, low-code, and Python-based approaches.
By the end of this training, participants will be able to:
- Identify key areas where agentic AI can drive process efficiency and innovation.
- Map workflows suitable for AI agent integration.
- Implement automation through APIs and orchestration tools.
- Integrate AI models into real business scenarios with measurable impact.
- Develop governance and monitoring structures for AI-driven operations.
Format of the Course
- Interactive lectures and practical demonstrations.
- Hands-on exercises and guided projects.
- Live implementation in a sandbox automation environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline
Introduction to Agentic AI in Business Automation
- What is agentic AI and why it matters for automation
- Overview of tools and frameworks for building intelligent agents
- Enterprise use cases: customer service, logistics, and marketing
Identifying Automation Opportunities
- Mapping current workflows and pain points
- Evaluating feasibility and ROI for AI-driven automation
- Defining success metrics and integration requirements
Designing Agentic Workflows
- Designing task-specific and orchestration-level agents
- Prompt design and logic structuring for automation agents
- Integrating decision-making and exception handling
Integrating Agents with Business Systems
- Connecting AI agents to CRMs, ERPs, and communication tools
- Using Zapier, Make, or Power Automate for orchestration
- Implementing API-based integrations with Python
Applied Use Cases
- Customer service automation and sentiment analysis
- Supply chain demand forecasting and vendor coordination
- Marketing campaign optimization using AI-driven insights
Governance, Security, and Monitoring
- Managing access control and data sensitivity
- Setting up monitoring dashboards and alerts
- Evaluating and auditing automated decisions
Hands-on Project: Building an Integrated AI Workflow
- Identifying a target process for automation
- Designing and implementing the AI agent
- Testing, evaluation, and optimization
Summary and Next Steps
Requirements
- Basic understanding of business workflows and process automation
- Familiarity with Python or API-based integrations
- Experience using productivity or automation tools
Audience
- Product managers seeking to identify automation opportunities
- Automation engineers implementing AI-driven workflows
- Business analysts designing data-informed business processes
Open Training Courses require 5+ participants.
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