How Can We Adapt Our IT Architecture for AI and Analytics?
Yes, it's time to rethink your IT architecture to support AI and analytics, moving beyond a focus on just transactional records. Connectivity Source can guide you in building a more adaptable infrastructure.
Why is a new IT architecture necessary for AI and analytics?
A new IT architecture is necessary because the potential of AI and big data is increasingly driving insights into everyday business processes across various departments like marketing, finance, and customer service. As organizations define new business processes, they require seamless data exchange between transactional and big data systems, which necessitates a rethinking of the overall IT framework.
How can organizations effectively integrate AI with existing IT systems?
Organizations should begin by documenting where AI and big data are currently utilized within their processes. This involves understanding the business processes that depend on AI and ensuring that these are integrated with traditional transactional systems. Regular regression testing is also essential to identify how failures in AI systems might impact other IT systems and business processes.
What role does cloud computing play in modern IT architecture?
Cloud computing plays a significant role by offering scalable solutions for AI and big data processing, which many companies are now transitioning to from on-premises systems. This shift allows organizations to easily adjust their resources as needed without the complexities of acquiring additional hardware or software, making it essential to account for both cloud-based and on-premises systems in the overall IT architecture.

How Can We Adapt Our IT Architecture for AI and Analytics?
published by Connectivity Source
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