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Course Outline
Introduction to Agentic AI in Business Automation
- Understanding agentic AI and its significance in automation
- Overview of essential tools and frameworks for building intelligent agents
- Enterprise applications: customer service, logistics, and marketing
Identifying Automation Opportunities
- Mapping existing workflows and identifying pain points
- Assessing feasibility and ROI for AI-driven automation
- Establishing success metrics and integration prerequisites
Designing Agentic Workflows
- Architecting task-specific and orchestration-level agents
- Structuring prompts and logic for automation agents
- Incorporating decision-making logic and exception handling
Integrating Agents with Business Systems
- Linking AI agents to CRMs, ERPs, and communication platforms
- Leveraging Zapier, Make, or Power Automate for orchestration
- Building API-based integrations using Python
Applied Use Cases
- Automating customer service and conducting sentiment analysis
- Predicting supply chain demand and coordinating with vendors
- Optimizing marketing campaigns through AI-driven insights
Governance, Security, and Monitoring
- Overseeing access control and data sensitivity
- Configuring monitoring dashboards and alert systems
- Reviewing and auditing automated decisions
Hands-on Project: Building an Integrated AI Workflow
- Selecting a target process for automation
- Designing and deploying the AI agent
- Conducting testing, evaluation, and optimization
Conclusion and Future Steps
Requirements
- Fundamental knowledge of business workflows and process automation
- Working familiarity with Python or API-based integrations
- Practical experience with productivity or automation software
Target Audience
- Product managers looking to uncover automation opportunities
- Automation engineers focused on deploying AI-driven workflows
- Business analysts designing data-centric business processes
21 Hours
Testimonials (1)
The trainer is patient and very helpful. He knows the topic well.