AI Architecture & Cost Structure Assessment

AI Architecture & Cost Structure Assessment — Free Assessment

Assessment Form

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AI Ownership & Inventory

Is there a complete, accurate inventory of all AI tools, models, and subscriptions used across the organisation?(Required)

Not at all

Basic / Partial

Mostly

Fully

Has shadow AI been assessed — AI tools adopted by teams outside the formal technology approval process?(Required)

Not at all

Basic / Partial

Mostly

Fully

AI Cost Visibility

Does the organisation have full visibility into total AI spend — cloud AI services, foundation model APIs, ML infrastructure, and AI SaaS?(Required)

Not at all

Basic / Partial

Mostly

Fully

Is AI spend tracked in near-real-time — not just at monthly finance reconciliation?(Required)

Not at all

Basic / Partial

Mostly

Fully

AI Vendor Dependency Risk

Has the degree of dependency on each major AI vendor been formally assessed?(Required)

Not at all

Basic / Partial

Mostly

Fully

Is there a single AI vendor whose removal would make critical AI capabilities unavailable?(Required)

Not at all

Basic / Partial

Mostly

Fully

Build vs Subscribe Strategy

Is there a documented framework for deciding whether to build, fine-tune, or subscribe for each AI capability?(Required)

Not at all

Basic / Partial

Mostly

Fully

Is the build-vs-subscribe framework consistently applied to all new AI capability decisions?(Required)

Not at all

Basic / Partial

Mostly

Fully

AI Cost Trajectory Management

Is the AI cost trajectory — month-on-month growth rate — tracked and reported to technology leadership?(Required)

Not at all

Basic / Partial

Mostly

Fully

Are AI cost efficiency targets set — cost per inference, cost per active user — and tracked?(Required)

Not at all

Basic / Partial

Mostly

Fully

Model Portability & Lock-in Avoidance

Are AI models built on open standards — ONNX, open weights, or vendor-neutral formats — where possible?(Required)

Not at all

Basic / Partial

Mostly

Fully

Are critical AI models deployable in a self-hosted environment — not solely dependent on vendor API availability?(Required)

Not at all

Basic / Partial

Mostly

Fully

AI Infrastructure Efficiency

Is AI compute utilisation tracked — are GPU/TPU resources right-sized to actual workload requirements?(Required)

Not at all

Basic / Partial

Mostly

Fully

Are spot or preemptible instances used for AI training workloads where interruption is acceptable?(Required)

Not at all

Basic / Partial

Mostly

Fully

MLOps & Model Lifecycle Maturity

Are ML models and training datasets versioned — can any model be reproduced from its training artefacts?(Required)

Not at all

Basic / Partial

Mostly

Fully

Is CI/CD for ML models implemented — automated testing and deployment pipelines for model updates?(Required)

Not at all

Basic / Partial

Mostly

Fully

AI Data Pipeline Architecture

Are data pipelines feeding AI training and inference reliable — SLA-governed with alerting for failures?(Required)

Not at all

Basic / Partial

Mostly

Fully

Are training datasets versioned and reproducible — can any model be retrained from the same data snapshot?(Required)

Not at all

Basic / Partial

Mostly

Fully

AI Security Architecture

Is access to AI models and training infrastructure controlled — only authorised users and systems can invoke models?(Required)

Not at all

Basic / Partial

Mostly

Fully

Is training data access controlled — no unauthorised access to sensitive training datasets?(Required)

Not at all

Basic / Partial

Mostly

Fully

AI Integration Architecture

Are AI capabilities exposed through well-designed APIs that abstract model implementation from consuming applications?(Required)

Not at all

Basic / Partial

Mostly

Fully

Are fallback mechanisms implemented for AI service unavailability — graceful degradation rather than failure?(Required)

Not at all

Basic / Partial

Mostly

Fully

AI Observability & Monitoring

Are AI model performance metrics — accuracy, precision, recall, F1 — monitored in production?(Required)

Not at all

Basic / Partial

Mostly

Fully

Is data drift and model drift monitored — are alerts triggered when input distributions shift significantly?(Required)

Not at all

Basic / Partial

Mostly

Fully