Redesigning Business Processes with GenAI

Reimagine workflows to maximize efficiency through AI augmentation.

Pillar

Process – Workflow, Governance, Risk & Efficiency

Overview

This course guides business leaders, process managers, and AI practitioners in redesigning existing workflows by integrating Generative AI technologies. Participants will learn to identify automation opportunities, optimize processes, and embed governance to ensure responsible and effective AI use.

Learning Objectives

Participants will be able to:

• Analyze current business processes for AI integration potential

• Design AI-augmented workflows to enhance productivity

• Implement governance frameworks for responsible AI use

• Manage risks associated with AI-driven process changes

• Measure and monitor the impact of AI on process efficiency

Target Audience

• Business process managers and analysts

• Operations leaders and project managers

• AI solution architects and practitioners

• Compliance and governance officers

Duration

20 hours over 4 days (5 hours per day)

Delivery Format

• Interactive lectures and process mapping exercises

• Case studies on AI-enabled process transformation

• Group workshops for governance and risk planning

Materials Provided

• Workflow redesign templates

• AI governance framework toolkit

• Risk management guidelines for AI processes

• Certificate of completion

Outcomes

• Develop AI-enhanced workflows tailored to business needs

• Embed governance and risk mitigation in process redesign

• Drive measurable improvements in operational efficiency

• Foster a culture of continuous AI-driven process innovation

Outline / Content

Day 1: Understanding Process Redesign with GenAI

• Fundamentals of AI augmentation in workflows

• Identifying automation and optimization opportunities

• Mapping current state workflows and pain points

Day 2: Designing AI-Augmented Workflows

• Principles of human-AI collaboration

• Creating future-state process models with GenAI

• Tools and platforms for workflow automation

Day 3: Governance and Risk Management

• Establishing AI governance structures

• Addressing compliance and ethical considerations

• Risk assessment and mitigation strategies

Day 4: Measuring Impact and Continuous Improvement

• Defining KPIs and performance metrics

• Monitoring AI process outcomes

• Continuous feedback loops and iterative redesign

• Final workshop: Designing an AI-augmented process pilot