Data acquisition represents the foundational economic challenge of enterprise AI implementation, often consuming 40-80% of total project budgets before a single model is trained. This article presents a comprehensive economic framework for understanding, planning, and optimizing data acquisition costs across different organizational contexts.
Oleh Ivchenko (Thu,) studied this question.