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Course Outline
Introduction to Agentic AI in Business Automation
- The concept of agentic AI and its significance for automation
- A review of tools and frameworks for creating intelligent agents
- Enterprise applications: customer service, logistics, and marketing
Identifying Automation Opportunities
- Analyzing existing workflows and identifying pain points
- Assessing the feasibility and ROI of AI-driven automation
- Establishing success metrics and integration prerequisites
Designing Agentic Workflows
- Crafting 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 performing sentiment analysis
- Predicting supply chain demand and coordinating with vendors
- Optimizing marketing campaigns with AI-driven insights
Governance, Security, and Monitoring
- Managing access controls and data sensitivity
- Configuring monitoring dashboards and alert systems
- Auditing and evaluating automated decisions
Hands-on Project: Building an Integrated AI Workflow
- Selecting a specific process for automation
- Designing and implementing the AI agent
- Conducting tests, evaluation, and optimization
Conclusion and Next Steps
Requirements
- A foundational understanding of business workflows and process automation
- Knowledge of Python or API-based integrations
- Practical experience with productivity or automation tools
Target Audience
- Product managers looking to uncover automation potential
- Automation engineers focused on deploying AI-driven workflows
- Business analysts responsible for designing data-informed processes
21 Hours
Testimonials (1)
The trainer is patient and very helpful. He knows the topic well.