AI & ML Research 8 Hours

Last updated: April 27, 2026, 11:30 AM ET

Enterprise AI & Data Infrastructure

Enterprises confronting meaningful AI adoption face hurdles that stem not from model performance but from the foundational state of their data infrastructure, leading many boardroom agendas to shift focus toward internal data remediation efforts. This challenge is mirrored in operational planning, where simulations reveal that a single forecast adjustment can propagate through five planning teams, causing significant financial erosion for retailers caught in the gap between Sales and Stores due to reliance on outdated spreadsheet models. Separately, in the realm of analytical modeling, evolving database techniques are prompting discussions about future development patterns, specifically contrasting the creation of explicit measures against calculation groups when leveraging features like User-Defined Functions in tabular models.