Deciding whether AI is right for a problem requires careful evaluation beyond whether it's technically possible. Start by asking if simpler solutions could work just as well with less complexity. Consider error tolerance: can users handle occasional mistakes, or would errors cause serious problems? Check data availability: AI needs good training examples that match how users actually work. Think about transparency requirements: some situations demand clear explanations that AI cannot give. Add up all costs including building, maintaining, monitoring, and retraining against expected benefits. Consider how users feel about AI handling this task. Some activities have personal or emotional meaning that users want to handle themselves.

Look at ethical implications: will AI treat all users fairly? Consider practical limits like processing speed or privacy rules. Create a checklist that weighs these factors based on your specific situation. Remember that AI should solve real user problems, not just showcase technology.