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Course Outline
Introduction to Agentic AI in Business Automation
- Understanding agentic AI and its significance in automation.
- An overview of tools and frameworks for creating 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.
- Defining success metrics and integration prerequisites.
Designing Agentic Workflows
- Architecting task-specific agents and orchestration-level systems.
- Structuring prompts and logic for automation agents.
- Incorporating decision-making logic and exception handling.
Integrating Agents with Business Systems
- Linking AI agents with CRMs, ERPs, and communication platforms.
- Leveraging Zapier, Make, or Power Automate for orchestration.
- Implementing API-based integrations using Python.
Applied Use Cases
- Automating customer service and analyzing sentiment.
- Predicting supply chain demand and coordinating vendors.
- Optimizing marketing campaigns using 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 target process for automation.
- Designing and implementing the AI agent.
- Testing, evaluating, and optimizing the workflow.
Summary and Next Steps
Requirements
- A foundational understanding of business workflows and process automation.
- Working knowledge of Python or API-based integrations.
- Practical experience with productivity or automation tools.
Target Audience
- Product managers looking to uncover automation opportunities.
- Automation engineers focused on deploying AI-driven workflows.
- Business analysts designing data-informed processes.
21 Hours
Testimonials (1)
The trainer is patient and very helpful. He knows the topic well.