AI Evaluation
AI Road Test Framework - Corporate Reference Guide
A structured reference guide for professional and corporate organisations evaluating AI adoption decisions, built around the seven-block AI Road Test Framework. Covers the full evaluation process from problem definition and AI capability assessment through to pilot design, failure diagnosis, and governance, with three detailed worked scenarios.
Published in 2026 by Masonsoft Technology Ltd, the AI Road Test Framework Corporate Reference Guide equips professional and enterprise organisations with a structured, evidence-based process for evaluating AI adoption decisions. It is designed for leaders who refuse to choose between uncritical enthusiasm and paralysed avoidance, offering a third path grounded in calibrated thinking.
The guide explains why poor AI decision-making is endemic, identifying three common patterns: solution-led adoption, binary thinking, and herd behaviour. It introduces a critical distinction between AI capabilities and specific AI-powered products, arguing that most failed pilots are tool or implementation failures rather than capability failures.
The Framework consists of a preliminary Context Calibration layer and seven evaluation blocks addressing problem definition, AI capability assessment, tool and vendor evaluation, implementation context, assumptions and risks, pilot design and failure diagnosis, and the human and governance dimensions. Each block contains structured prompts designed to surface implicit assumptions and make them testable before resources are committed.
Three practice scenarios demonstrate the Framework applied to a retail SME assessing a customer service chatbot, a manufacturer considering predictive maintenance AI, and a law firm evaluating AI-assisted document review, showing how the same process can produce different yet defensible outcomes depending on context.