Course Outline

Introduction to Agentic AI in Business Automation

  • What is agentic AI and why it matters for automation
  • Overview of tools and frameworks for building intelligent agents
  • Enterprise use cases: customer service, logistics, and marketing

Identifying Automation Opportunities

  • Mapping current workflows and pain points
  • Evaluating feasibility and ROI for AI-driven automation
  • Defining success metrics and integration requirements

Designing Agentic Workflows

  • Designing task-specific and orchestration-level agents
  • Prompt design and logic structuring for automation agents
  • Integrating decision-making and exception handling

Integrating Agents with Business Systems

  • Connecting AI agents to CRMs, ERPs, and communication tools
  • Using Zapier, Make, or Power Automate for orchestration
  • Implementing API-based integrations with Python

Applied Use Cases

  • Customer service automation and sentiment analysis
  • Supply chain demand forecasting and vendor coordination
  • Marketing campaign optimization 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 optimization

Summary and Next Steps

Requirements

  • Basic understanding of business workflows and process automation
  • Familiarity with Python or API-based integrations
  • Experience using productivity or automation tools

Audience

  • Product managers seeking to identify automation opportunities
  • Automation engineers implementing AI-driven workflows
  • Business analysts designing data-informed business processes
 21 Hours

Testimonials (1)

Upcoming Courses

Related Categories