AI TRAININGS · ISO 22301:2019 · ISO/IEC 42001:2023
AI in Business Continuity Management
Design, govern and test AI-supported continuity capabilities while preserving accountable decisions, fallback modes and evidence aligned with ISO 22301.
Who should attend
AI in Business Continuity
- BCMS owners and business continuity managers
- Operational resilience and crisis leaders
- Risk, internal audit and compliance teams
- AI product, data and technology owners
Learning outcomes
- 01
Inventory AI use cases and dependencies inside BCMS scope
- 02
Extend BIA and risk assessment without treating model output as fact
- 03
Define human authority, fallback and minimum-service modes
- 04
Build test scenarios for provider, data and model failure
- 05
Select evidence and metrics for management review
- 06
Connect AI governance with ISO 22301 and ISO/IEC 42001
Detailed training outline
8 modules, each tied to a working output.
Design, govern and test AI-supported continuity capabilities while preserving accountable decisions, fallback modes and evidence aligned with ISO 22301.
- 01
BCMS baseline and AI boundary
Establish the published ISO 22301 baseline, intended outcomes and the difference between AI-enabled support and accountable continuity decisions.
- 02
AI use-case and dependency inventory
Map models, data sources, prompts, retrieval stores, providers, operators and downstream processes that can affect continuity outcomes.
- 03
AI-aware business impact analysis
Add AI-supported activities, maximum tolerable disruption, data freshness and manual-workaround assumptions to the BIA while requiring human validation.
- 04
Continuity risk and failure modes
Assess unavailable models, degraded quality, hallucinated advice, poisoned or stale data, concentration risk, access loss and uncontrolled change.
- 05
Continuity strategies and fallback design
Select alternate providers, offline references, deterministic tools, manual procedures, capacity reserves and explicit stop conditions.
- 06
Response, recovery and crisis decision support
Define activation authority, approved inputs, output verification, escalation, communication approval, evidence capture and return-to-normal criteria.
- 07
Exercises, tests and adversarial scenarios
Test provider outage, corrupted retrieval, prompt manipulation, unsafe recommendation, unavailable approver and simultaneous cyber disruption.
- 08
Metrics, review and continual improvement
Define availability, fallback success, decision override, data freshness, recovery performance, unresolved risk and exercise-action metrics.
Participant working pack
Participant working pack
Training supports competence and implementation planning. It is not certification, accredited auditor training, legal advice or a conformity assessment.
- AI dependency register
- AI-aware BIA annex
- Failure-mode and control worksheet
- Fallback and minimum-service playbook
- Tabletop scenario and action log
- 90-day implementation roadmap
Authoritative references
Authoritative references
Working knowledge of the relevant management system is helpful; licensed standards remain the controlling source.
AI TRAININGS
Request dates and delivery format
Training supports competence and implementation planning. It is not certification, accredited auditor training, legal advice or a conformity assessment.