AI Readiness Evaluation
Understanding the gap between current state architecture and AI requirements.
Business Objectives & Alignment
Readiness starts with intent. We assess whether the stated business objectives for an AI project are clearly defined and measurable. Without a defined target, evaluating the success of a pilot is impossible.
Data Availability & Quality
AI models require relevant information to function correctly. We review whether the necessary data is currently captured, stored in accessible formats, and maintained to an adequate standard of quality. Poor data quality inherently leads to poor AI outputs.
Access Permissions & Sensitive Information
When connecting intelligent systems to internal networks, strict access permissions must be enforced. We review how sensitive information is currently handled and discuss methodologies for ensuring AI tools respect existing user privileges, preventing unauthorised data exposure.
Testing Methods & Human Review
Operational readiness includes having the resources to verify AI outputs. We help design testing methods and establish workflows that guarantee a human-in-the-loop, ensuring critical decisions are never left entirely to autonomous systems.