AI projects like Google’s Gemini Enterprise unlock powerful productivity and use cases. Yet, enterprises fail to move AI pilots to production and scale.
Unstructured data has always been the bane of security leaders, with analysts reporting 80% of enterprise data is unstructured, and growing 55%-65% annually. In fact, almost half of enterprise AI decision makers quote data security, privacy, and compliance as key barriers to AI adoption.
AI solutions like Gemini Enterprise are, although critical to growth and innovation, but these tools don’t know:
- Where does sensitive data reside?
- Who has access to it?
- Is ROT data skewing AI responses?
- Can we enforce controls before indexing occurs?
AI adoption tends to come to a halt when enterprises fail to have upstream security, governance, and compliance controls before indexing occurs.
We’ve put together this ebook, “Take the Data Risk Out of AI”, to demonstrate how Securiti gives enterprises a practical framework to automatically classify sensitive data, visually map access with its Data Command Graph, and enforce pre-index policies. This enables organizations to get a clean, governed data ready for safe Gemini Enterprise adoption.
