The executive checklist: 30 questions before scaling AI
A verification routine across five dimensions — data, risk, integration, people and cost — to separate enthusiasm from readiness.
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A verification routine across five dimensions — data, risk, integration, people and cost — to separate enthusiasm from readiness.
Wave sequencing, exit criteria per phase, what to centralize and what to federate — and the mistakes that cost a year.
Baseline, metrics per use case, efficiency gain versus accumulated asset — and how to avoid endless pilots that never reach production.
A decision matrix by data sensitivity and criticality: total cost, sovereignty, open versus proprietary models, and exit strategy.
What to record, how long to keep it, and how to answer an auditor, a customer or a regulator without depending on your vendor's goodwill.
Roles, a risk-based approval matrix, an acceptable use policy and a use-case inventory — the minimum executive governance for scaling without surprises.
Legal basis, minimization, anonymization, impact assessments and model-vendor clauses — what changes when AI enters the workflow.
Answer quality is a data and permission problem, not a model problem. What changes when the index must respect who can see what.
Legacy integration patterns explained for the people who approve budgets — without rewriting the core or becoming hostage to a proprietary connector.
How to capture, version and curate prompts, responses and decisions so every AI use improves the next one — instead of vanishing at the end of the session.
How a corporate AI gateway becomes the single point of egress — identity, routing, DLP on request and response, cost limits and shadow AI blocking.
The real path of a corporate prompt: retention, model training, subprocessors and data residency — and the questions that belong in the contract.
What actually replaces the per-turn prompt in agentic systems — and where the risk goes when no one reviews the wording anymore.
Individual licenses create personal gain and organizational loss. What a company forfeits when the knowledge produced with AI dies inside the chat window.
Put it to work
Everything we cover here — AI governance, legacy system integration, audit trails and preserved corporate knowledge — is available on the e.works platform at eworks.cloud.
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