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Course Outline
Introduction to Agentic AI in Business Automation
- Understanding agentic AI and its significance for automation
- Surveying tools and frameworks for developing intelligent agents
- Enterprise applications: customer service, logistics, and marketing
Identifying Automation Opportunities
- Analyzing existing workflows and associated pain points
- Assessing the feasibility and ROI of AI-driven automation
- Establishing success metrics and integration prerequisites
Designing Agentic Workflows
- Architecting task-specific agents and orchestration-level systems
- Crafting prompts and structuring logic for automation agents
- Incorporating decision-making capabilities and exception handling
Integrating Agents with Business Systems
- Linking AI agents with CRMs, ERPs, and communication platforms
- Leveraging Zapier, Make, or Power Automate for workflow orchestration
- Building API-based integrations using Python
Applied Use Cases
- Automating customer service and analyzing sentiment
- Predicting supply chain demand and coordinating with vendors
- 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
- Conducting testing, evaluation, and optimization
Summary and Next Steps
Requirements
- A foundational understanding of business workflows and process automation
- Familiarity with Python or API-based integration techniques
- Practical experience utilizing productivity or automation tools
Audience
- Product managers aiming to uncover automation opportunities
- Automation engineers focused on 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.