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But, for many organizations, the data required for training may not be available in a unified way.
As this technology continues to advance, enterprises are at an inflection point.
First, understand where your critical data and applications are and how those locations will leverage AI.
Then equip those strategic locations with secured hardware and appropriate high-performance capabilities (accelerators and high-performance storage).
Use a consistent set of platform technologies data management, AI, observability, security, etc.
across each of these locations, to speed time to AI value.
This platform approach is what we at IBM call hybrid by design.
CTO and General Manager of Innovation for IBM Infrastructure.
For example, a business marketingarmmight use AI to develop customer segmentation and generate personalized offers.
This is what we call hybrid by default.
This is just the beginning of whats possible with a hybrid-by-design architecture.
If these changes are not made, enterprises are at risk of incurring or increasing tech debt.
Additionally, adopting AI before this debt is paid can result in less effective AI and more distributed data.
Lets take technical debt for example.
However, hybrid by design is more than just modernizing existing technology.
It is a gradual approach that preserves existing resources and streamlines priorities.
To harness generative AIs revolutionary potential, enterprises need to take a revolutionary approach to organizing their IT assets.
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The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc.
