Building AI starts with defining a clear problem and success metric, collecting quality data, and choosing appropriate model families. Iterate with prototypes, validate on holdout sets, and design for explainability and monitoring. Integrate models with business workflows, plan for drift, and establish human oversight. Responsible deployment balances performance gains with ethics and compliance.