AI-Powered Automation for Operations & Service Delivery

Accelerate repetitive and high-volume tasks using GenAI bots and agents.

Pillar

Process – Workflow, Governance, Risk & Efficiency

Overview

This course focuses on leveraging Generative AI-powered automation to streamline operations and enhance service delivery. Participants will learn how to deploy AI bots and agents to handle routine tasks, reduce errors, and increase productivity across various business functions.

Learning Objectives

Participants will be able to:

• Identify operational tasks suitable for AI automation

• Design and implement GenAI-driven automation workflows

• Configure and manage AI bots and virtual agents

• Evaluate automation impact on efficiency and service quality

• Address operational risks and ensure seamless integration

Target Audience

• Operations managers and process owners

• IT and automation specialists

• Customer service and support leaders

• AI implementation and project teams

Duration

20 hours over 4 days (5 hours per day)

Delivery Format

• Hands-on automation design workshops

• Case studies on AI automation success stories

• Interactive bot configuration and deployment sessions

Materials Provided

• Automation workflow templates

• AI bot configuration guides

• Performance measurement frameworks

• Certificate of completion

Outcomes

• Accelerate business processes through AI automation

• Enhance service delivery speed and accuracy

• Minimize human errors in repetitive tasks

• Drive continuous improvement in operational workflows

Outline / Content

Day 1: Identifying Automation Opportunities

• Overview of AI automation in operations and services

• Mapping repetitive and high-volume tasks

• Prioritizing automation use cases

Day 2: Designing AI Automation Workflows

• Principles of AI-powered automation

• Tools and platforms for GenAI bots and agents

• Workflow integration and orchestration

Day 3: Configuring and Deploying AI Bots

• Setting up virtual agents and chatbots

• Managing AI interactions and exceptions

• Ensuring reliability and scalability

Day 4: Measuring Impact and Continuous Improvement

• Defining KPIs for automation success

• Monitoring performance and user feedback

• Iterative optimization and scaling strategies

• Final workshop: Develop an AI automation plan for a key operation