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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
21 Hours
Testimonials (1)
We got to use the tools.