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Course Outline
Introduction to Agentic AI in Business Automation
- Understanding the definition of agentic AI and its significance in automation
- A review of the tools and frameworks used to build intelligent agents
- Enterprise applications: customer service, logistics, and marketing
Identifying Automation Opportunities
- Mapping existing workflows and identifying pain points
- Assessing the feasibility and ROI of AI-driven automation
- Establishing success metrics and integration requirements
Designing Agentic Workflows
- Creating task-specific and orchestration-level agents
- Crafting prompts and structuring logic for automation agents
- Incorporating decision-making processes 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
- Executing API-based integrations using Python
Applied Use Cases
- Automating customer service and analyzing sentiment
- Forecasting demand and coordinating vendors in the supply chain
- Optimizing marketing campaigns with 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
- Testing, evaluating, and refining the solution
Summary and Next Steps
Requirements
- Fundamental knowledge of business workflows and process automation
- Proficiency with Python or API-based integrations
- Practical experience with productivity or automation software
Audience
- Product managers looking to uncover automation opportunities
- Automation engineers focused on deploying AI-driven workflows
- Business analysts creating data-driven business processes
21 Hours
Testimonials (1)
The trainer is patient and very helpful. He knows the topic well.