How many companies intentionally refuse to use AI to get their work done faster and more efficiently? Probably none: the advantages of AI are too great to deny.
The benefits AI models offer to organizations are undeniable, especially for optimizing critical operations and outputs. However, generative AI also comes with risk. According to the IBM Institute for Business Value, 96% of executives say adopting generative AI makes a security breach likely in their organization within the next three years.
CISA Director Jen Easterly said, “We don’t have a cyber problem, we have a technology and culture problem. Because at the end of the day, we have allowed speed to market and features to really put safety and security in the backseat.” And no place in technology reveals the obsession with speed to market more than generative AI.
AI training sets ingest massive amounts of valuable and sensitive data, which makes AI models a juicy attack target. Organizations cannot afford to bring unsecured AI into their environments, but they can’t do without the technology either.
To bridge the gap between the need for AI and its inherent risks, it’s imperative to establish a solid framework to direct AI security and model use. To help meet this need, IBM recently announced its Framework for Securing Generative AI. Let’s see how a well-developed framework can help you establish solid AI cybersecurity.
Securing the AI pipeline
A generative AI framework should be designed to help cust ..
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