Setting initial expectations

User expectations form before they even open your product. Marketing messages, app store descriptions, and word of mouth all shape what people expect AI to do. Promising magical capabilities sets users up for disappointment when they hit real limitations. Clear expectation setting starts with benefits, not technology. Instead of "Our AI uses advanced neural networks," try "Draft emails faster with smart suggestions." Users care about solving problems, not implementation details. Focus on what they can accomplish.

Be upfront about limitations from the start. A fitness AI should mention that it gives general guidance, not medical advice. These boundaries help users work effectively within system capabilities. Early messaging should prepare users for the learning relationship. Let them know the system improves with feedback. Explain that initial suggestions might feel generic but become personalized over time. This frames early mistakes as part of the journey, not failures. Setting realistic expectations creates space for positive surprises. When users expect basic features and discover helpful additions, trust grows. When they expect miracles and hit limitations, trust breaks.^[1]