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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 use cases: 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

  • Creating task-specific and orchestration-level agents.
  • Crafting prompts and structuring logic for automation agents.
  • Integrating decision-making capabilities and exception handling.

Integrating Agents with Business Systems

  • Connecting AI agents to CRMs, ERPs, and communication platforms.
  • 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.
  • Marketing campaign optimization leveraging 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 optimization.

Summary and Next Steps

Requirements

  • Fundamental understanding of business workflows and process automation.
  • Familiarity with Python or API-based integrations.
  • Experience utilizing productivity or automation tools.

Audience

  • Product managers aiming to identify automation opportunities.
  • Automation engineers responsible for implementing AI-driven workflows.
  • Business analysts focused on designing data-informed business processes.
 21 Hours

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