Poor data infrastructure remains the primary bottleneck for companies deploying AI at scale. While consumer tools excel, MIT Technology Review reports that enterprises must rebuild their data stacks to make internal models functional. This shift forces a pivot from chasing new models to cleaning legacy datasets. Practitioners must prioritize data hygiene over tool acquisition.