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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

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