A city's citizen chatbot needs change after nearly every town hall as residents request new intents and languages. Which delivery approach is most appropriate for that uncertainty?
Select an answer to reveal the explanation.
Short Explanation
When town halls keep rewriting what the chatbot must understand, locking a year of intents on day one is like printing a menu before you know who is coming to dinner. Adaptive delivery expects that learning and reshapes the backlog. Freezing early or ignoring feedback fights the uncertainty.
Full Explanation
High uncertainty and frequent requirement change favor an adaptive approach that inspects feedback and revises priorities. A citizen chatbot shaped by successive town halls fits that pattern better than a fully frozen predictive scope. Suppressing feedback or treating the product like a one-shot physical pour does not address shifting civic needs.