Business Continuity Planning in AI-Integrated Systems

Prepare resilient workflows that include AI dependencies.

Pillar

Process – Workflow, Governance, Risk & Efficiency

Overview

This course focuses on developing robust business continuity plans that account for the unique challenges and dependencies introduced by integrating Generative AI systems. Participants will learn to identify AI-related risks, design contingency strategies, and ensure operational resilience in AI-augmented environments.

Learning Objectives

Participants will be able to:

• Understand AI-specific risks impacting business continuity

• Assess vulnerabilities in AI-integrated workflows

• Develop contingency plans addressing AI system failures

• Implement risk mitigation strategies for AI dependencies

• Coordinate cross-functional response plans for AI disruptions

Target Audience

• Business continuity and risk management professionals

• IT and AI operations teams

• Process and compliance managers

• Senior leadership and strategy teams

Duration

20 hours over 4 days (5 hours per day)

Delivery Format

• Interactive lectures and case study reviews

• Scenario-based tabletop exercises

• Group workshops for plan development

Materials Provided

• Business continuity plan templates for AI systems

• Risk assessment checklists

• Scenario playbooks

• Certificate of completion

Outcomes

• Identify and mitigate AI-specific operational risks

• Develop actionable business continuity plans incorporating AI

• Enhance organizational resilience to AI system disruptions

• Foster collaboration across teams for crisis management

Outline / Content

Day 1: Understanding AI Dependencies and Risks

• Overview of AI integration in business processes

• Common points of failure and vulnerabilities

• Impact of AI disruptions on operations

Day 2: Risk Assessment and Impact Analysis

• Conducting AI-specific risk assessments

• Identifying critical AI components and workflows

• Prioritizing risks based on business impact

Day 3: Designing Continuity and Contingency Plans

• Developing backup and failover strategies for AI systems

• Creating communication and escalation protocols

• Integrating AI risk mitigation into existing continuity frameworks

Day 4: Testing, Training, and Continuous Improvement

• Conducting tabletop exercises and simulations

• Training teams on AI continuity procedures

• Reviewing and updating plans based on lessons learned

• Workshop: Draft a business continuity plan for an AI-integrated process

• Group feedback and discussion