For most businesses a GPU is not really expensive, particularly if the results are important to the business.
Chasing a single metric is certainly too narrow but getting the best results often does matter in a professional context too. While Kaggle can go overboard on massive ensembles using a state-of-the-art approach to the problem is often warranted outside of Kaggle.
Electronic medical records. Anything in healthcare/medical, financial services, legal. There's a long way from the "worst text classification" to "sufficient text classification" in most real world use cases. With a reasonable budget you can relabel data and work around subjectivity.
Chasing a single metric is certainly too narrow but getting the best results often does matter in a professional context too. While Kaggle can go overboard on massive ensembles using a state-of-the-art approach to the problem is often warranted outside of Kaggle.