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Course Outline

Foundations of Agentic AI in Business Automation

  • Defining agentic AI and its significance for automation
  • Overview of essential tools and frameworks for creating intelligent agents
  • Enterprise applications: customer support, logistics, and marketing

Pinpointing Automation Potential

  • Analyzing existing workflows and identifying bottlenecks
  • Assessing the feasibility and ROI of AI-driven automation
  • Establishing success criteria and integration prerequisites

Architecting Agentic Workflows

  • Designing agents for specific tasks and orchestration levels
  • Structuring prompts and logic for automation agents
  • Incorporating decision-making logic and exception management

Connecting Agents to Enterprise Systems

  • Linking AI agents with CRMs, ERPs, and communication platforms
  • Leveraging Zapier, Make, or Power Automate for workflow orchestration
  • Executing API-based integrations using Python

Practical Use Cases

  • Automating customer service and conducting sentiment analysis
  • Predicting supply chain demand and coordinating with vendors
  • Optimizing marketing campaigns through AI-generated insights

Governance, Security, and Oversight

  • Regulating access controls and handling sensitive data
  • Configuring monitoring dashboards and alert systems
  • Reviewing and auditing automated decisions

Capstone Project: Developing an Integrated AI Workflow

  • Selecting a target process for automation
  • Designing and deploying the AI agent
  • Conducting tests, evaluations, and optimizations

Recap and Future Directions

Requirements

  • Fundamental knowledge of business workflows and process automation
  • Basic proficiency with Python or API-based integrations
  • Prior experience utilizing productivity or automation software

Target Audience

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

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