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Course Outline

Foundations of Agentic AI in Business Automation

  • Understanding agentic AI and its significance in automation
  • Review of key tools and frameworks for developing intelligent agents
  • Enterprise applications in customer service, logistics, and marketing

Discovering Automation Potential

  • Analysing existing workflows and identifying bottlenecks
  • Assessing feasibility and Return on Investment (ROI) for AI-driven automation
  • Establishing success metrics and integration prerequisites

Architecting Agentic Workflows

  • Creating task-specific agents and orchestration-level structures
  • Formulating prompt design and logic structures for automation agents
  • Incorporating decision-making processes and exception handling

Connecting Agents with Business Ecosystems

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

Practical Application Scenarios

  • Automating customer service and conducting sentiment analysis
  • Forecasting supply chain demand and coordinating with vendors
  • Optimising marketing campaigns through AI-driven insights

Ensuring Governance, Security, and Oversight

  • Regulating access control and managing data sensitivity
  • Configuring monitoring dashboards and alert systems
  • Reviewing and auditing automated decisions for accuracy

Practical Project: Constructing an Integrated AI Workflow

  • Selecting a specific process for automation
  • Designing and deploying the AI agent
  • Conducting testing, evaluation, and iterative optimisation

Conclusion and Future Directions

Requirements

  • A fundamental grasp 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 aiming to uncover automation opportunities
  • Automation engineers focused on deploying AI-driven workflows
  • Business analysts crafting data-driven business processes
 21 Hours

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