The rapid adoption of artificial intelligence tools, such as large language models, has outpaced governance and security measures, posing significant risks to users and businesses. Since the public debut of ChatGPT nearly four years ago, users have been uploading sensitive data, including corporate and financial records, to these models without adequate safeguards. While catastrophic consequences have been largely avoided, the security implications of this trend are substantial. IBM's developments in large language models, for example, are reshaping both the capabilities and risk surfaces of these technologies1. As AI tools transition from assisted to autonomous, the need for robust security protocols becomes increasingly pressing. The lack of effective governance and security measures surrounding AI adoption poses a significant threat to sensitive data, making it essential for practitioners to prioritize the development of robust security protocols to mitigate these risks.