The Writing’s on the Wall

After more than twenty years in business continuity, I have never seen such a fundamental shift. The uncomfortable truth is that focusing only on traditional risks misses half the picture. AI systems fail differently; their ripple effects can devastate. Organisations already want BCM professionals fluent in continuity planning and AI risk management.

Two Standards, One Reality

ISO 22301 still guides continuity: assess risks, build plans, test, improve. ISO IEC 42001, released in 2023, adds responsible AI management. Treating it as someone else’s problem will damage your career. The two standards fit together. Both rely on a risk-based process approach, stakeholder engagement, and continual improvement, so your BCM skills transfer directly to AI governance. Both standards demand documentation, defined roles, and evidence of continual improvement. They differ in scope. Traditional BCM covers external threats and operational failures, whereas AI governance addresses algorithmic bias, model failure, and data quality. By aligning both views, you gain a single dashboard for operational and algorithmic resilience, reducing duplication. Combined they deliver truly comprehensive modern risk management.

The Skills Gap and Opportunity

Organisations now seek professionals who can map AI dependencies, understand model failure, and craft recovery procedures for AI-driven processes. They pay premium salaries because this expertise is scarce. They also need people who can translate technical failure reports into language executives understand and regulators accept. Your current skills in impact analysis, crisis communication, and stakeholder coordination remain valuable during AI incidents; you simply need sufficient AI understanding to apply them.

Career Transformation

Successful companies weave AI governance into existing risk programmes. I know BCM professionals who became Chief Resilience Officers by mastering both traditional and digital risks. Others moved into specialised AI risk management roles or bridged technical teams and leadership. One practitioner I coached leveraged incident post mortems to convince leadership to fund an integrated resilience roadmap. They all began with strong BCM foundations and added AI literacy.

Getting Started

You do not need to become a data scientist. First, identify where your organisation already uses AI such as recommendation engines, automated decisions, predictive analytics, and fraud detection. Map these systems like any critical process. What happens if they fail? How will you spot bad outputs? Who monitors them? ISO IEC 42001 offers structure, but you can begin informally. Build AI risk awareness within your existing framework.

The Learning Curve

AI governance is less technical than you expect. You must grasp machine learning models, data pipelines, and bias, but you do not need to code. Treat it like cybersecurity for BCM: understand attacks without being a penetration tester. For example, understand how drift in training data erodes model accuracy over time, or how incomplete data pipelines can silently block predictions. Focus on failure modes, data quality, and detecting poor performance. These are risk management questions, not technical ones.

Planning Your Next Steps

Step One:

• Read the ISO/IEC 42001 standard.
• Look for specialised training programs designed for BCM professionals transitioning to AI governance.
• Start attending webinars covering AI risk from a business-continuity perspective.
• Join professional groups where these topics are discussed.

Step Two:

• Get hands-on experience.
• Volunteer for AI-related risk assessments in your organisation.
• Shadow data-science or IT teams to understand how AI systems are deployed and monitored.

Step Three:

• Pursue formal certification in AI governance.
• Consider whether your organisation needs someone to lead integrated risk-management efforts.
• Position yourself as the expert who understands both traditional and emerging risks.

Looking Forward

AI governance within business continuity is now baseline. Organisations that ignore AI risks will face regulators, failures, competitive disadvantage, and eroded customer trust, slowing future innovation. For BCM professionals this is both challenge and opportunity: extend expertise into unfamiliar territory and become indispensable during digital transformation. Mastering both will future-proof your career. AI is already central to business. The real question is whether you are ready to manage the associated risks.

Training and Implementation Resources

• ISO/IEC 42001 Lead Implementer Training
  • Comprehensive program covering practical implementation of AI management systems
  • Designed specifically for risk-management professionals
  • Cost: USD $599
  • ISO/IEC 42001 Lead Implementer
• ISO/IEC 42001 Lead Auditor Certification
  • Advanced certification for professionals conducting AI management-system audits
  • Provides credibility for consulting and assessment roles
  • Cost: USD $599
  • ISO/IEC 42001 Lead Auditor
• ISO/IEC 42001 Document Kit Templates
  • Ready-to-use templates for implementing AI-governance frameworks
  • Integrates with existing BCM documentation systems
  • Cost: USD $699
  • ISO/IEC 42001 Document Kit Templates