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Course Outline

Foundations of Agentic AI in Business Automation

  • Defining agentic AI and its significance in modern automation
  • A comprehensive overview of tools and frameworks for developing intelligent agents
  • Enterprise application examples: customer service, logistics, and marketing

Strategic Identification of Automation Opportunities

  • Mapping existing workflows and identifying operational pain points
  • Assessing feasibility and return on investment (ROI) for AI-driven solutions
  • Establishing success metrics and defining integration requirements

Architecting Agentic Workflows

  • Designing both task-specific agents and orchestration-level architectures
  • Crafting prompts and structuring logic for effective automation agents
  • Incorporating decision-making logic and exception handling mechanisms

Connecting Agents with Core Business Systems

  • Synchronizing AI agents with 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 interactions and performing sentiment analysis
  • Predicting supply chain demand and coordinating vendor activities
  • Optimizing marketing campaigns through AI-driven insights

Governance, Security, and Operational Monitoring

  • Managing access controls and safeguarding data sensitivity
  • Configuring monitoring dashboards and alerting systems
  • Auditing and evaluating automated decision-making processes

Capstone Project: Constructing an Integrated AI Workflow

  • Selecting a target process for automation implementation
  • Designing and deploying the AI agent solution
  • Conducting testing, evaluation, and optimization cycles

Conclusion and Strategic Next Steps

Requirements

  • Fundamental comprehension of business workflows and process automation concepts
  • Proficiency with Python or API-based integration techniques
  • Practical experience utilizing productivity or automation software

Target Audience

  • Product managers aiming to uncover new automation opportunities
  • Automation engineers focused on deploying AI-driven workflows
  • Business analysts crafting data-informed operational processes
 21 Hours

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