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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 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 requirements

Designing Agentic Workflows

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

Integrating Agents with Business Systems

  • Connecting AI agents to CRMs, ERPs, and communication tools
  • 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
  • Optimising marketing campaigns 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 optimisation

Summary and Next Steps

Requirements

  • A foundational understanding of business workflows and process automation
  • Knowledge of Python or API-based integrations
  • Experience with productivity or automation tools

Target Audience

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

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