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Course Outline

Foundations of Agentic AI in Business Automation

  • Understanding agentic AI and its significance for modern automation
  • Survey of key tools and frameworks for developing intelligent agents
  • Exploring enterprise applications in customer service, logistics, and marketing

Uncovering Automation Opportunities

  • Analyzing existing workflows to identify bottlenecks and pain points
  • Assessing the viability and return on investment for AI-driven solutions
  • Establishing success metrics and defining integration prerequisites

Architecting Agentic Workflows

  • Creating both task-specific agents and broader orchestration-level agents
  • Structuring prompts and logic to optimize automation agent performance
  • Embedding decision-making logic and exception handling mechanisms

Connecting Agents to 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

Practical Application Scenarios

  • Automating customer service interactions with sentiment analysis
  • Enhancing supply chain demand forecasting and vendor coordination
  • Optimizing marketing campaigns through AI-driven insights

Governance, Security, and Oversight

  • Overseeing access control and managing data sensitivity
  • Configuring monitoring dashboards and alert systems
  • Reviewing and auditing automated decision-making processes

Practical Exercise: Constructing an Integrated AI Workflow

  • Selecting a specific business process for automation
  • Designing and deploying the corresponding AI agent
  • Conducting testing, evaluation, and iterative optimization

Conclusion and Future Directions

Requirements

  • Foundational knowledge of business workflows and process automation
  • Proficiency with Python or API-based integrations
  • Practical experience utilizing productivity or automation software

Target Audience

  • Product managers looking to uncover automation potential
  • Automation engineers focused on deploying AI-driven workflows
  • Business analysts crafting data-driven business processes
 21 Hours

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