AI Adoption Filter

The structured evaluation framework that determines whether a specific operational process is a candidate for AI automation, as distinct from no-code automation or full human judgment. The AI adoption filter asks: 

• Is the process’s output subjective or objective? 
• Is the training data sufficient and bias-free? 
• What is the cost of an incorrect AI output?
• Is the process stable enough for model training? 

AI adoption without this filter consistently produces automation that fails silently producing outputs that look correct but are systematically wrong.