Securing AI Innovation Without Sacrificing Pace – FireTail Blog

Apr 23, 2025 – – AI security is a crtical issue in today’s landscape. With developers, teams, employees and lines of business racing ahead to compete, security teams consistently fall short in an ecosystem where new risks are rising up every day. The result is that we are seeing an unprecedented amount of AI breaches in 2025.According to Capgemini, 97% of organizations suffered incidents related to generative AI initiatives in the past year. It is unclear whether these incidents were all breaches, or whether some were merely vulnerabilities, however, around half of these organizations reported the loss impact would be estimated at $50M+ per incident. This shows the scale of data involved, as well as that each incident would indicate a systemic flaw, likely exposing an entire data set.So how do developers and security teams work together to continue innovating in the AI space, without sacrificing security? The issue is complicated and requires a multilayered approach.From Code to Cloud…One of the best ways to ensure your AI is secure is to start in the design phase. At FireTail, we talk a lot about protecting your cyber assets from “code to cloud.” Designing your models with security in mind enables you to stay ahead of threats instead of having to play a constant game of whackamole when new risks pop up. Security should be a prime concern from code to cloud.Development teams and security teams need to work together on the design phase to ensure the mutual success of them both. We’ve talked before about the growing developer/security team gap, but in order to have a holistic security posture, this gap needs to be bridged from the beginning by involving security teams in the early stages of design and development.Visibility- If you can’t see it, you can’t secure it.It is common knowledge that visibility and discovery are the cornerstones of any strong cybersecurity posture. Having full visibility allows security teams to stay ahead of threats by spotting vulnerabilities and misconfigurations before they pop up.Everyone in your team should know what AI models you are using, what they are being used for, what information is okay to input into them and what is not, et cetera. And security teams need to be vigilant in monitoring AI interactions and activity. A centralized dashboard can help to keep all of these interactions in one place, in order to ensure nothing slips between the cracks.MonitoringAny strong AI security posture should involve constant mo

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