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Key Takeaways AI data has emerged as valuable intellectual property, and failing to protect it can cause catastrophic loss for an organization.
To protect your AI data, you must first identify and classify your “crown jewel” assets. Then, choose your strategic backup architecture.
You should also steer your organization away from manual backups and opt for backups to be integrated with machine learning ops.
The breakneck pace of AI deployment across enterprises is creating a monumental challenge for executives and company boards. In contrast to traditional IT systems, AI data and related ecosystems, which encompass everything from LLM models and training data to custom prompt data, have emerged as valuable intellectual property. They often represent millions of dollars in investment and months or even years of engineering effort.
Any loss of AI data can cause catastrophic loss for an organization, especially those that have integrated crucial processes, such as decision-making and risk analysis, with AI systems. If AI systems get compromised or the integrity of their results comes into doubt, it can cause loss of both customer trust and revenue.
In some edge cases, you may even need to build everything up from scratch. Thus, executives need to make crucial decisions around securing AI data and enabling business continuity.
In this guide, we offer a comprehensive framework for leaders entrusted with implementing AI initiatives with a core focus on strategic decisions.
Step 1: Identify and classify your “crown jewel” AI assets
As an executive, the first action that you need to undertake is getting your team to perform a comprehensive audit of what actually needs to be secured. It is important to realize the full scope of AI infrastructure and its complexity.
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