A tailored course, built for your situation
Mastering ISO 27001 for Agentic Automation Practitioners
A structured path to implementing and governing AI-driven automation with recognized compliance rigor
The situation this course is for
Teams rush to deploy intelligent automation but skip the governance layer, leading to rework, failed certifications, and eroded client trust. The gap isn't technical, it's structural. Without a compliance-first design approach, even the most advanced automations are seen as risky, not transformative.
Who this is for
Senior advisory practitioner at a global services firm, specializing in automation or AI implementation, with exposure to compliance frameworks and client-facing delivery.
Who this is not for
Entry-level RPA developers, pure software engineers without client advisory experience, or internal IT teams without governance responsibilities.
What you walk away with
- Design automation workflows with embedded ISO 27001 control points
- Position automation as a premium advisory offering, not a cost-cutting tool
- Lead client conversations that tie AI implementation to audit readiness
- Deliver documentation that passes internal and external compliance review without revision
- Increase engagement margins by bundling compliance assurance into automation design
The 12 modules (with all 144 chapters)
- Defining information assets in agent-based systems
- Mapping ISO 27001 clauses to automation components
- Identifying custodianship in distributed agent networks
- Classifying data flows in non-human workflows
- Setting the baseline for auditability in AI actions
- Linking security policy to agent behavior rules
- Integrating risk assessment into automation planning
- Documenting asset inventories for agent ecosystems
- Establishing ownership for AI-generated data
- Applying confidentiality principles to bot interactions
- Ensuring integrity in autonomous decision chains
- Availability requirements for always-on agent systems
- Embedding compliance into automation design sprints
- Defining approval gates for agent deployment
- Control objectives for third-party AI components
- Version control and audit trails for bot logic
- Change management processes for agent updates
- Access control policies for bot-to-bot communication
- Credential management in headless automation
- Segregation of duties in agent teams
- Monitoring privileged actions in AI workflows
- Logging requirements for autonomous decisions
- Retention policies for agent-generated records
- Incident response planning for rogue agents
- Threat modeling for intelligent agents
- Identifying single points of failure in agent chains
- Assessing data leakage through automation pathways
- Evaluating unauthorized learning in adaptive bots
- Third-party risk in agent marketplace integrations
- Compliance drift in long-running autonomous workflows
- Human override mechanisms and their risks
- Agent collusion and emergent behavior risks
- Bias propagation in automated decision trees
- Model drift detection in production agents
- Supply chain risks in pre-trained agent models
- Legal and reputational exposure from AI errors
- Security by design in agent architecture
- Code review standards for automation scripts
- Static and dynamic analysis of agent logic
- Hardening execution environments for bots
- Secure API integration patterns
- Input validation for agent-to-agent messages
- Error handling without data exposure
- Secure storage of agent credentials
- Environment segregation for testing agents
- Penetration testing for automation workflows
- Secure deployment pipelines for bots
- Compliance validation before production rollout
- Principles of least privilege for bots
- Service account lifecycle management
- Machine-to-machine authentication protocols
- Role-based access for agent teams
- Time-bound access for temporary agents
- Multi-factor authentication for critical actions
- Just-in-time access for elevated privileges
- Agent identity federation across platforms
- Revocation mechanisms for decommissioned bots
- Audit logging of access decisions
- Monitoring for anomalous bot behavior
- Detecting and blocking unauthorized agent access
- Designing immutable logs for agent decisions
- Timestamp accuracy across distributed agents
- Centralized logging for multi-platform bots
- Log retention aligned with compliance standards
- Ensuring log integrity and non-repudiation
- Correlating human and agent actions in audits
- Querying logs for forensic investigations
- Automated anomaly detection in action logs
- Redacting sensitive data in shared logs
- Access controls for log review workflows
- Generating audit-ready agent activity reports
- Demonstrating compliance through log evidence
- Defining what constitutes an agent incident
- Incident classification for AI-driven failures
- Escalation paths for rogue automation
- Human-in-the-loop intervention protocols
- Containment strategies for agent outbreaks
- Forensic investigation of agent behavior
- Business impact assessment for automation failures
- Recovery procedures for disrupted workflows
- Post-mortem analysis of AI incidents
- Updating controls based on incident learnings
- Reporting obligations for automated breaches
- Regulator communication for AI incidents
- Due diligence for AI component vendors
- Contractual obligations for agent behavior
- SLAs for autonomous system performance
- Right-to-audit clauses for third-party bots
- Monitoring vendor compliance with ISO 27001
- Data handling standards in external agents
- Licensing risks in AI model usage
- Transparency requirements for black-box agents
- Exit strategies for third-party automation
- Dependency mapping for agent ecosystems
- Contingency planning for vendor failures
- Onboarding and offboarding third-party agents
- Statement of Applicability for agent systems
- Writing security policies for AI workflows
- Control implementation statements for bots
- Evidence collection for automated controls
- Mapping automation to ISO 27001 controls
- Documenting exceptions and compensating controls
- Preparing for internal audit review
- Client-facing compliance narratives
- Version control for compliance documents
- Auditor walkthroughs of automation controls
- Generating compliance reports for stakeholders
- Maintaining documentation across updates
- GDPR implications for agent data processing
- HIPAA compliance in healthcare automation
- SOX controls for financial reporting bots
- DORA requirements for EU financial automation
- Sector-specific risk assessments for agents
- Handling regulated data in AI workflows
- Audit trails for compliance-critical decisions
- Human review requirements for regulated outputs
- Data residency in cross-border automation
- Regulator engagement on AI use cases
- Justifying automation in conservative sectors
- Balancing innovation with compliance caution
- Standardizing agent templates for reuse
- Centralized policy enforcement for bots
- Governance as code for automation controls
- Automated compliance validation pipelines
- Cross-team coordination for agent rollout
- Training developers on secure automation
- Monitoring compliance at scale
- Managing technical debt in agent networks
- Versioning and deprecation strategies
- Resource optimization in agent fleets
- Cost management for large-scale automation
- Sustainability considerations for AI agents
- Framing compliance as a competitive advantage
- Communicating automation value to risk officers
- Building trust with audit and legal teams
- Client storytelling for premium automation
- Pricing automation with embedded compliance
- Differentiating from low-cost bot farms
- Case studies of successful ISO 27001 automation
- Speaking the language of governance
- Evangelizing secure automation internally
- Influencing client requirements
- Shaping automation strategy at leadership level
- Future-proofing skills in AI governance
How this maps to your situation
- Design phase of new automation initiative
- Pre-audit preparation for automation project
- Client proposal development with compliance emphasis
- Post-incident review and control enhancement
Before vs. after
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 90 minutes per module, designed for completion over a weekend or weekday evenings.
How this compares to the alternatives
Unlike generic RPA courses or broad compliance trainings, this program is tailored to practitioners bridging AI automation and information security, offering actionable control patterns aligned with ISO 27001 and real-world advisory delivery scenarios.
Frequently asked
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.