Operationalizing GenAI in Business Workflows

Embed GenAI tools into day-to-day processes across departments.

Pillar

Process – Workflow, Governance, Risk & Efficiency

Overview

This course guides participants through the practical steps of integrating Generative AI technologies into everyday business workflows. It covers identifying opportunities, designing AI-augmented processes, and managing change to improve efficiency and outcomes across departments.

Learning Objectives

Participants will be able to:

• Identify key business processes suited for GenAI integration

• Design and implement AI-augmented workflows

• Manage cross-functional collaboration for AI adoption

• Address challenges in embedding GenAI tools operationally

• Measure and optimize the impact of GenAI in workflows

Target Audience

• Business process managers and analysts

• AI solution architects and developers

• Operations and transformation leaders

• Department heads and team leads

Duration

20 hours over 4 days (5 hours per day)

Delivery Format

• Interactive workshops with process mapping

• Case studies of successful GenAI workflow integration

• Group exercises for change management and adoption planning

Materials Provided

• Workflow design templates and checklists

• Case study documentation and best practices

• AI integration roadmaps and measurement frameworks

• Certificate of completion

Outcomes

• Embed Generative AI into operational workflows effectively

• Drive efficiency and innovation across business units

• Overcome barriers to AI adoption at the process level

• Continuously improve AI-augmented business operations

Outline / Content

Day 1: Identifying AI Integration Opportunities

• Overview of business workflows and AI potential

• Process mapping and opportunity analysis

• Prioritizing AI integration use cases

Day 2: Designing AI-Augmented Workflows

• Principles of AI workflow design

• Tools and platforms for GenAI integration

• Collaboration between AI and business teams

Day 3: Change Management for AI Adoption

• Strategies to foster user acceptance

• Training and support mechanisms

• Managing resistance and challenges

Day 4: Measuring and Optimizing Impact

• Defining KPIs and success metrics

• Monitoring AI workflow performance

• Iterative improvement and scaling

• Final workshop: Develop an operationalization plan for a business unit