Have you heard of the Shadow AI risk, but are gracefully ignoring it? Less recommended.
If you were to ask your employees, they would say that AI is amazing and they want to work with it more and more. If you ask your security manager, they will tell you they don't sleep at night. There are CISOs who prefer to avoid using AI and avoid problems, and there are those who understand that the organization must move forward and enable usage, but some of them try to "save" money and not invest in advanced monitoring solutions. In reality? If AI usage is permitted without a monitoring solution, it could end up costing a fortune.
Either way, employees will use artificial intelligence – the only question is whether there is control over it or if the organization is exposed to severe operational, legal, and financial damages under the radar.
When you don't have a watchful eye on what is running on endpoints and in browsers, the organization is flooded with critical risks
1. Leak of source code, classified data, and trade secrets: uploading sensitive files or lines of code to public models without supervision.
2. Exposure of passwords and access keys (API Keys): Including this information within an innocent chat query.
3. Severe regulatory and privacy violations: Working with external AI vendors without security arrangements, audits, or compliance procedures.
4. Advanced security threats and unmonitored agents: Exploitation of Prompt Injection and granting over-privileges to AI agents connected to core systems.
5. Business decisions based on misinformation: Relying on model "hallucinations," alongside risks of copyright and intellectual property infringement.
6. Total blindness in cyber incidents: Lack of logging and monitoring that makes breach detection difficult, delays the investigation, and skyrockets remediation costs and reputational damage.
Employees are already using AI. The only question is who is managing it?
Avoiding the adoption of an advanced monitoring tool is not a cost-saving measure, but rather a hidden and much greater expense.
💡 How N-sight AI gives you back control (and your money)?
1. Comprehensive endpoint-level discovery: Immediate detection of applications, browser extensions, and local models, including attribution to vendor, category, and recent activity.
2. DNS-level AI traffic identification: Scanning and classifying AI services that devices access to understand usage patterns—without compromising content privacy.
3. Central AI Adoption Dashboard: Centralization of all insights in one place for reporting, regulatory compliance, and the enforcement of strict security policies.
4. A time savings of ~95% compared to manual work: Automatic troubleshooting and analysis of findings 97.5% faster than traditional methods.
So what are you waiting for?
