3 steps to designing a strong data foundation for AI implementation to transform CX


  • The complexity of crafting a viable data infrastructure that is fit-for-purpose for AI and IA adoption cannot be underestimated. Let’s not forget most organizations are constantly leveraging historic data.

  • It is reasonable for any sizable business - enterprise or government institution to have volumes of data being added on a daily basis.


Thus, ensuring the data being collected by organisations is relatable across multiple systems, and not sitting in silos (one system, process, department, etc.) is vital. The correlation of data across functions and processes allows an organization to achieve a holistic view of the customer. Thus data structuring is an important choice organizations need to make when implementing IA and AI applications. However, complete data synthesis and visibility is an ongoing challenge for most organisations.
Ensuring the data being collected by organisations is relatable across departments, and not sitting in silos is important.