Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Protecting sensitive data is no longer just a compliance objective. It has become a prerequisite for adopting cloud services, enabling AI, and maintaining customer trust. Yet many organizations still struggle to balance innovation with effective data governance. A 2025 Forrester Total Economic Impact study commissioned by Microsoft found that organizations using mature data protection capabilities, including data loss prevention (DLP), achieved a 30% reduction in the likelihood of data breaches.

Enterprise RAG pipelines have a recall stage and a precision stage. The retriever handles recall. The reranker handles precision. Skipping the reranker, or misplacing security controls around it, is where most accuracy and data exposure problems begin. The retriever’s job is to pull back every document that might be relevant. The reranker’s job is to find, from that candidate set, the documents that actually answer the question.

Access control has become significantly more complex as enterprises adopt cloud platforms, AI applications, and distributed workforces. A user’s identity alone is no longer enough to determine whether they should access sensitive data. Factors such as device posture, data sensitivity, location, and business context all influence the right decision. This shift is driving widespread adoption of attribute-based access control, a model that evaluates multiple attributes before granting access.

Security teams often evaluate ChatGPT by examining its outputs. The greater risk, however, lies in the information employees submit before the model generates a single response. As generative AI becomes a big part of daily business operations, prompts increasingly contain confidential customer data, proprietary source code, legal documents, and strategic plans.

Authentication used to be a login form. Then it became IAM: identity providers, roles, federation, lifecycle. Then it became Zero Trust: no built-in trust, every request checked in context. Each step did not replace the last so much as fold it into a bigger runtime decision. The login still happens, but it is now one input to a constant, context-based check.