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Course Outline
Foundations of Agentic AI in Business Automation
- Defining agentic AI and its significance for automation
- Overview of essential tools and frameworks for creating intelligent agents
- Enterprise applications: customer support, logistics, and marketing
Pinpointing Automation Potential
- Analyzing existing workflows and identifying bottlenecks
- Assessing the feasibility and ROI of AI-driven automation
- Establishing success criteria and integration prerequisites
Architecting Agentic Workflows
- Designing agents for specific tasks and orchestration levels
- Structuring prompts and logic for automation agents
- Incorporating decision-making logic and exception management
Connecting Agents to Enterprise Systems
- Linking AI agents with CRMs, ERPs, and communication platforms
- Leveraging Zapier, Make, or Power Automate for workflow orchestration
- Executing API-based integrations using Python
Practical Use Cases
- Automating customer service and conducting sentiment analysis
- Predicting supply chain demand and coordinating with vendors
- Optimizing marketing campaigns through AI-generated insights
Governance, Security, and Oversight
- Regulating access controls and handling sensitive data
- Configuring monitoring dashboards and alert systems
- Reviewing and auditing automated decisions
Capstone Project: Developing an Integrated AI Workflow
- Selecting a target process for automation
- Designing and deploying the AI agent
- Conducting tests, evaluations, and optimizations
Recap and Future Directions
Requirements
- Fundamental knowledge of business workflows and process automation
- Basic proficiency with Python or API-based integrations
- Prior experience utilizing productivity or automation software
Target Audience
- Product managers looking to uncover automation opportunities
- Automation engineers deploying AI-driven workflows
- Business analysts crafting data-informed business processes
21 Hours
Testimonials (1)
The trainer is patient and very helpful. He knows the topic well.