Technology & Architecture addresses how AI systems are deployed, secured, and integrated within your organisation’s technical infrastructure. This covers whether AI tools are sanctioned and enterprise-managed (rather than staff using uncontrolled consumer services), integration with identity and access management systems, alignment with security frameworks, scalability of the infrastructure, and architectural standards for AI deployment. It also includes considerations like multi-cloud strategies, sandboxed experimentation environments, and ensuring AI systems can be audited and monitored.
The risk here is “shadow AI”—staff using free or unsanctioned AI tools that bypass enterprise security, leak sensitive data, or create ungoverned dependencies. This dimension evaluates the security, scalability, and control of your AI technology infrastructure, and whether AI tools are enterprise-managed, integrated with identity and access management (IAM), and aligned with architectural standards.
Why It Matters
Uncontrolled AI tools expose organisations to data leakage, compliance risks, and operational vulnerabilities.
Maturity Levels
| Basic | Standard | Advanced | Leading |
|---|---|---|---|
| Staff using free or unsanctioned tools with no enterprise oversight. | Enterprise-controlled AI platforms with basic security and access controls. | Multi-cloud AI infrastructure integrated with IAM and enterprise security frameworks. | Sandboxed environments for experimentation, with continuous updates aligned to Partner-in-the-Loop principles. |
📥 Related Resources & Templates
Downloadable templates, examples, and frameworks to help you implement this dimension.
AI Architecture Standards
Technical architecture standards and best practices for AI system design, integration, and infrastructure.
Identity & Access Management for AI
PremiumIAM policy and access control matrix specifically designed for AI systems, models, and data access.