[Stanley]

Why Your GenAI Strategy Demands an All-Inclusive Data Modernization

Enterprise Generative AI strategies are failing because they are being built on incompatible legacy data warehouses. The core problem is that "piecemeal" data migrations fail to transfer the intricate business logic and orchestration embedded in these old systems. This "missing scope" breaks business continuity. The only viable path forward is an "all-inclusive" modernization that migrates both data and business logic together as a prerequisite for any successful AI implementation.


https://hackernoon.com/why-your-genai-st...source=rss

[Vectura]

Solid read “all-inclusive data modernization” is exactly what a lot of GenAI projects skip before hitting trouble. If your data’s messy, siloed, or half-old, any AI strategy becomes a house of cards.

[JoshAllen]

You can’t build smart AI on old and outdated systems.

To make this work, people need to upgrade everything. Data, logic, etc.