If you are an IT Operations Lead or Head of Secure Development at a digital bank, this playbook was built for you.
As a senior technology leader in a regulated financial institution, you are under increasing pressure to modernize internal tooling and accelerate developer productivity while maintaining strict adherence to financial sector compliance standards. Generative AI presents a compelling opportunity to streamline operations, automate repetitive tasks, and prototype internal systems faster than ever before. However, deploying AI-augmented development practices in a production IT environment introduces new risks around data governance, model transparency, and regulatory scrutiny. Without a structured approach, your team risks non-compliance, audit findings, or operational disruptions due to poorly governed AI usage.
Traditional consulting routes to establish AI governance can cost between EUR 80,000 and EUR 250,000 through major advisory firms, with delivery timelines stretching over six to nine months. Alternatively, building an internal team of three to five specialists to develop policies, controls, and implementation frameworks from scratch would require at least six months of dedicated effort. This playbook delivers the same foundational structure, control mappings, and operational templates for a one-time cost of $395, enabling your team to begin secure implementation immediately.
What you get
| Phase | File Type | Description | File Count |
| Assessment & Scoping | Domain Assessment | 30-question evaluation covering risks and readiness in each of seven core domains: data governance, model lifecycle, access control, audit logging, third-party AI use, developer policy adherence, and incident response planning | 7 |
| Evidence Collection | Runbook | Step-by-step guide for gathering and organizing documentation required to demonstrate compliance with AI governance controls across NIST AI RMF, ISO/IEC 42001, and SOC 2 | 1 |
| Audit Preparation | Playbook | Structured workflow for preparing internal and external audits, including evidence review checklists, auditor Q&A preparation, and control validation timelines | 1 |
| Implementation Planning | RACI Template | Pre-defined responsibility assignment matrix for AI-augmented development roles including AI oversight officer, security lead, compliance reviewer, and developer leads | 1 |
| Implementation Planning | WBS Template | Work breakdown structure outlining 120 discrete tasks across six phases of AI-augmented tooling rollout, with estimated durations and dependency mapping | 1 |
| Cross-Reference | Mapping Matrix | Comprehensive crosswalk between control objectives in NIST AI RMF, ISO/IEC 42001, and SOC 2 Trust Services Criteria, enabling unified policy development | 1 |
| Policy & Governance | Policy Templates | 50-page collection of editable governance documents including AI usage policy, model validation procedure, developer code of conduct, and incident escalation protocol | 50 |
| Total | 64 |
Domain assessments
Each of the seven domain assessments contains 30 targeted questions designed to evaluate current state maturity and identify control gaps in AI-augmented development practices:
- Data Governance: Evaluates data classification, retention, and access controls for prompts, outputs, and training data used in internal AI tooling.
- Model Lifecycle Management: Assesses versioning, testing, deployment, and deprecation processes for generative AI models used in development environments.
- Access and Authentication: Reviews role-based access controls, multi-factor authentication, and session management for AI development platforms.
- Audit Logging and Monitoring: Measures the completeness and retention of logs for AI-generated code, prompt history, and system interactions.
- Third-Party AI Services: Examines contractual terms, data processing agreements, and security assurances for external AI APIs and platforms.
- Developer Policy Compliance: Tests awareness and adherence to internal policies on AI use, code review requirements, and prohibited use cases.
- Incident Response and Remediation: Validates procedures for detecting, reporting, and mitigating incidents involving AI-generated code or system behavior.
What this saves you
| Activity | Time Required Without Playbook | Time Required With Playbook | Estimated Hours Saved |
| Develop AI Risk Assessment Framework | 320 hours | 40 hours | 280 |
| Map Controls Across NIST, ISO, SOC 2 | 200 hours | 25 hours | 175 |
| Create Evidence Collection Process | 160 hours | 20 hours | 140 |
| Draft AI Usage Policies | 120 hours | 30 hours | 90 |
| Prepare for Internal Audit | 100 hours | 25 hours | 75 |
| Build Implementation Work Plan | 80 hours | 15 hours | 65 |
| Total Estimated Savings | 1,000 hours | 155 hours | 845 hours |
Who this is for
- IT Operations Managers in digital banks overseeing internal tooling and developer infrastructure
- Heads of Secure Software Development responsible for AI policy and code integrity
- Compliance Officers tasked with validating AI governance controls for regulatory reporting
- Chief Information Security Officers evaluating AI-related cyber risks in development environments
- Technology Risk Managers conducting control assessments for AI-augmented systems
- Internal Audit Leads preparing for reviews of AI implementation in IT operations
- AI Governance Committee Members establishing cross-functional oversight frameworks
Cross-framework mappings
This playbook includes direct control mappings to the following regulatory and industry frameworks:
- NIST Artificial Intelligence Risk Management Framework (AI RMF 1.0)
- ISO/IEC 42001 Artificial Intelligence Management System
- SOC 2 Trust Services Criteria (Security, Availability, Processing Integrity)
What is NOT in this product
- This playbook does not include custom consulting services or direct implementation support.
- It does not provide integration code, API connectors, or software tools for AI platforms.
- There are no pre-configured dashboards, monitoring systems, or logging agents included.
- The templates are not pre-filled with your organization's data or policies.
- It does not cover customer-facing AI applications such as chatbots or credit decisioning models.
- Regulatory filings or submissions are not generated or reviewed as part of this product.
- Training sessions, workshops, or certification programs are not included.
Lifetime access and satisfaction guarantee
You receive lifetime access to the playbook with no subscription required and no login portal to manage. The files are delivered in standard document formats that you can store, back up, and use indefinitely. If this playbook does not save your team at least 100 hours of manual compliance work, email us for a full refund. No questions, no friction.
About the seller
The creator has spent 25 years developing structured compliance frameworks for highly regulated industries. They have analyzed 692 regulatory and industry standards and built 819,000+ cross-framework control mappings used by 40,000+ practitioners across 160 countries. Their work focuses on translating complex regulatory requirements into practical implementation tools for technical and compliance teams in financial services, healthcare, and critical infrastructure sectors.
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