Zscaler, a leader in Secure Exchange Architecture, has provide some shocking insights. automated alarming from their cloud environment where they reported substantial data loss prevention (DLP) violations. The study estimates over 4 million DLP violations have occurred. Zscaler has proven its ability to block most if not all attempts to leak sensitive enterprise data into generative AI applications. This data paints a stark picture of this critical information. It spans financial documents, PII, source code, and even health information.
As this year’s study clearly points out, one of the most pressing issues marked by the new phrase “Shadow AI,” rapidly becoming the great blind spot in enterprise security. Employees want to increase their productivity. While they have begun to leverage generative AI tools in their workflows, it is not in an officially sanctioned manner. As such, adoption of AI by businesses has skyrocketed since its release in the public domain late last year.
Earlier in 2024, Zscaler’s ThreatLabz team uncovered an amazing new discovery. This year, they looked at 36x more traffic for AI/ML than the year before. Through this extensive analysis, we were able to compile a comprehensive list of 800+ unique AI applications that organizations are actively using today. With the explosion of these applications comes a significant ability to misuse personal data, leading to alarming potential abuses.
Zscaler is in a special place as far as the traffic flow. This variety gives the company an unparalleled perspective to effectively spot and combat these violations. Its approach to security is based on context-aware, policy-driven governance based on zero trust principles. With a zero trust foundation, Zscaler believes organizations need to trust no one implicitly, requiring constant and context-based assessment of all data access.
AI technologies are rapidly being integrated into the day-to-day workflows. There are a few key actions organizations should start taking to mitigate the risk of a data breach. Zscaler underscores the imperative for robust Data Loss Prevention (DLP) plans. These strategies not only shield sensitive information, but they enable enterprises to stay on the right side of industry regulations.
Zscaler’s discoveries are a cue for enterprises to be on their toes amid the fine balance of automated AI adoption. This trend away from official channels to integrate AI tools leaves organizations with a substantial amount of data loss risk. It creates challenges to adhere to emerging data governance policies.
