Full Spectrum AI Security: FireTail's Platform Update for the AI-Enabled Workforce

Stop guessing how your team is using AI and gain full visibility into Shadow AI while empowering your workforce to use new tools safely and productively.

The rise of generative AI has changed how businesses operate. In almost every company, leaders are looking for ways to use AI to work faster and smarter. However, this shift has created a major challenge for security teams. Most of the AI activity inside an organization is currently happening without any oversight from IT or security departments.

AI is the future, and if security teams don’t allow AI adoption, they risk being seen as the department of no. But as everyone rushes to incorporate AI, most security teams struggle to keep visibility of all AI usage, and understand the risks involved.

These challenges fall into two major categories: securing production environments (code, cloud, applications = AI “Workload”) and governing employee usage of AI tools (AI “Workforce”).

The Workload: Securing the apps, APIs, models, and data pipelines you build.
The Workforce: Governing how your employees use third-party AI tools (like ChatGPT, Claude, or Midjourney) to handle user requests and corporate data.

At FireTail, our first focus was on securing Workload AI adoption. Given our extensive background in API security this made sense, as the vast majority of workload AI adoption happens across APIs.

Workload vulnerabilities, while fewer in number, are much more dangerous when exploited. Our skills, experience and focus helped us to quickly develop a comprehensive set of capabilities for workload AI security. While that remains important, it is only half of the story. There is a second, equally critical area that needs attention: the Workforce.

The Workforce includes every employee using tools like ChatGPT, Claude, or Gemini to write emails, analyze data, or summarize meetings. To stay secure, companies need a "Full Spectrum" approach. This means protecting both what the company builds and how its employees work.

The Problem of Shadow AI in the Modern Office

Most employees don’t wait for permission to use tools that make their jobs easier. This has led to the rise of "Shadow AI,” or AI services that have not been vetted or approved by the IT department.

Shadow AI is so hard to track because the browser has become the new operating system. Employees access AI tools directly through Chrome or Edge. Because these tools are easy to sign up for, they often bypass traditional security filters.

Standard security tools might show that a user logged into a website, but they cannot see what happened next. They cannot see if an employee is pasting sensitive company secrets into a public prompt. They also cannot see if proprietary documents are being uploaded to train external models. This visibility gap is where the greatest risks live.

Why Blocking AI is Not the Answer

When a new technology presents a risk, many security teams try to block it entirely. With AI, this approach often backfires. If employees feel they need AI to keep up with their workload, a total block will simply drive them to use personal devices or unmanaged accounts. This makes the security team’s job even harder as the activity moves off the corporate network.

The goal should not be to stop AI usage, but to govern it. Governance allows a company to say "yes" to AI while keeping data safe. This allows for a more nuanced approach where different teams have different levels of access based on their specific needs and risks.

Three Pillars of Workforce AI Security

To manage an AI-enabled workforce effectively, companies need three core capabilities:

Discovery: You cannot protect what you cannot see. Companies need a way to find every AI service being used across the organization. This includes seeing which users have signed up for which tools and how often they use them.
Observability: Beyond just knowing a tool is being used, security teams need to see the context. This means understanding the types of data being sent to AI models and identifying potential policy violations in real time.
Governance: Once you have visibility, you need the power to act. This includes the ability to set specific rules for different groups, such as allowing the creative team to use image generators while restricting the legal team from uploading contracts to public LLMs.

FireTail’s Latest Innovations for the Workforce

FireTail has launched a major update to its platform to address these specific workforce challenges. Our goal is to provide a single platform that handles both workload and workforce security. Here is a look at the key features and how they work:

Visibility

If you can’t see it, you can’t secure it. Our latest platform update significantly boosts FireTail’s workforce AI capabilities with end-to-end discovery through deep integrations.

Google Workspace Sync & SSO Insights
Browser Extension Visibility and Policy Enforcement
Endpoint Visibility and Policy Enforcement

These integrations work together to ensure you get deeper context, monitoring, visibility and policy enforcement for all your AI usage and interactions across the workforce alike.

Governance

FireTail’s new governance features allow for control rather than blocking.

Policy Enforcement: Set rules based on who is allowed to access what
Bulk Actions: Manage alerts and policy violations at scale
Automated Guardrails: Detect PII or sensitive IP from being put into unauthorized LLMs

The New AI Risk Dashboard

We are thrilled to unveil the FireTail AI Risk Dashboard. Designed for CISOs and GRC teams, this dashboard centralizes all workforce AI risks into one place.

Identify Hotspots: See which groups and users are using Shadow AI.
Detections: See PII, data leakage and more.
Data-Driven Decisions: Understand the inherent risks of the most popular LLMs, and make informed decisions about which to allow and which to block.

Ready to see the Full Spectrum in action?

By combining these tools, FireTail offers the most complete solution for the AI-enabled enterprise. Our full spectrum approach combines comprehensive workload and workforce AI security capabilities to help you embrace AI adoption across the entire organization with clarity and confidence.