Most organizations today use commercial AI systems rather than hosting or training their own models. That includes platforms like OpenAI, Gemini, Microsoft Copilot, and Anthropic. This shift changes the security problem. Instead of focusing on testing model vulnerabilities, organizations have far less control over the underlying system. The primary controllable surface becomes the data they send into these tools. That means security risks move from model integrity to data exposure, governance, and sharing behavior. Traditional AI security assumptions—like auditing or hardening models—become less central when the model is effectively outsourced. If organizations can’t meaningfully control the model anymore, how should they rethink AI security strategy? Subscribe to our podcasts: https://securityweekly.com/subscribe #DataSecurity #SecurityWeekly #Cybersecurity #InformationSecurity #AI #InfoSec
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