A data engineer is preparing a tabular dataset for a k-nearest neighbors model. The dataset includes 'annual_income' (values from 20,000 to 500,000) and 'age' (values from 18 to 90). During evaluation, the team notices that predictions are almost entirely driven by income differences, while age has negligible influence, even though domain experts consider age highly relevant. What is the MOST appropriate feature preparation step to address this?