As organizations embrace generative AI, there are a host of benefits that they are expecting from these projects—from efficiency and productivity gains to improved speed of business to more innovation in products and services. However, one factor that forms a critical part of this AI innovation is trust. Trustworthy AI relies on understanding how the AI works and how it makes decisions.
According to a survey of C-suite executives from the IBM Institute for Business Value, 82% of respondents say secure and trustworthy AI is essential to the success of their business, yet only 24% of current generative AI projects are being secured. This leaves a staggering gap in securing known AI projects. Add to this, the ‘Shadow AI’ present within the organizations, it makes the security gap for AI even more sizable.
Challenges to securing AI deployment
Organizations have a whole new pipeline of projects being built that leverage generative AI. During the data collection and handling phase, you need to collect huge volumes of data to feed the model and you’re providing access to several different people, including data scientists, engineers, developers and others. This inherently presents a risk by centralizing all that data in one place and giving many people access to it. This means that generative AI is a new type of data s ..
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