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Course Outline
Introduction to Agentic AI in Business Automation
- Understanding agentic AI and its significance for automation
- Overview of tools and frameworks for constructing 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 requirements
Designing Agentic Workflows
- Designing task-specific and orchestration-level agents
- Prompt engineering and logic structuring for automation agents
- Incorporating decision-making and exception handling
Integrating Agents with Business Systems
- Connecting AI agents to CRMs, ERPs, and communication tools
- Leveraging Zapier, Make, or Power Automate for orchestration
- Implementing API-based integrations using Python
Applied Use Cases
- Customer service automation and sentiment analysis
- Supply chain demand forecasting and vendor coordination
- Optimising marketing campaigns using AI-driven insights
Governance, Security, and Monitoring
- Managing access control and data sensitivity
- Setting up monitoring dashboards and alerts
- Evaluating and auditing automated decisions
Hands-on Project: Building an Integrated AI Workflow
- Identifying a target process for automation
- Designing and implementing the AI agent
- Testing, evaluation, and optimisation
Summary and Next Steps
Requirements
- A foundational understanding of business workflows and process automation
- Knowledge of Python or API-based integrations
- Experience with productivity or automation tools
Target Audience
- Product managers looking to identify automation potential
- Automation engineers implementing 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.