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USE CASE
AI security and governance
AI didn't wait for your strategy. See what's running, decide who gets in, prove what it did, and control what it can reach.
For nearly 40 years, Citrix has met enterprises where they are. DOS apps, client-server, the web, mobile, cloud. Each time, someone said to rewrite everything. Each time, our customers kept their apps, and we wrapped them in access and security. AI is the same playbook, with one difference: some of the users are AI agents.
Four questions you can't answer yet
You answer all four for every other app you run. For AI, most companies can’t answer one.
VISIBILITY
Where is AI running, and who's using it?
It came in from every direction. Personal accounts on work laptops. Assistants switched on inside the SaaS apps you already pay for. Agents acting for your employees, using their logins. Ask for a complete inventory and you’ll get a partial list.
ACCESS
Whose login is it using?
An agent runs with the permissions of whoever started it, so it can open everything they can. A personal account on a corporate laptop looks like any other login. To most identity controls, both look like your employee.
GOVERNANCE
What did it do, and who answers for it?
Prompts, responses, and tool calls go straight to the cloud, into logs you don't own. Ask what your AI did last Tuesday and you'll be asking the vendor. Regulators and auditors will expect you to know.
CONTROL
What can it reach, and what's it costing?
Connect an assistant to corporate storage and it gets whatever that connection allows. A growing share of those connections runs over Model Context Protocol (MCP), which wasn't built for enterprise control. Usage costs keep climbing with no clear owner.
Among users accessing AI on corporate devices, 67% use non-corporate accounts. Shadow AI's share of detected non-malicious insider actions rose fourfold year over year in Verizon's 2025 data loss prevention dataset.
BENEFITS
Point the controls you already have at the AI you already have
For existing Citrix customers, there's no new infrastructure to deploy and no applications to rebuild. Protection is applied through configuration across the device, network, browser, session, and data layers you already operate. When your AI strategy shifts, the controls shift with it. Your investment stays tied to business outcomes, not to a single AI vendor's roadmap.
VISIBILITY
See what's actually running
Start with an accurate picture of the AI in your environment, who relies on it, and how people use their applications and processes day to day. The findings usually reshape the plan, starting with the unapproved tools whole departments now depend on. Every decision that follows builds on this baseline.
Discover every AI tool: Approved or not, each one identified and classified.
Map usage to people: Which employees use which tools and models, and how often.
Understand how work gets done: The applications people rely on, the workflows they follow, and where AI shows up along the way.
ACCESS
Give every person and every agent a verified identity
Tie each AI session to a corporate identity and confirm the device is trusted before it connects. Agents get identities of their own instead of borrowing an employee's. The user experience doesn't change.
Verified before access: Device posture and context checked on every AI session.
No anonymous AI: Corporate identity required, personal accounts blocked.
Agents scoped to the task: Limit each agent's permissions to what its task requires.
GOVERNANCE
Know what your AI did and who's accountable
Every AI session is recorded against a person, an application, and a model. When something goes wrong, the record is already there, so your answer comes with evidence instead of guesswork.
Prove what happened: Prompts and tool calls captured in one audit trail and sent to your SIEM, with session recording available by policy.
Set policy once: Approved models defined by team, personal AI subscriptions blocked.
Assign ownership: Every agent runs under its own identity, with a named person accountable for it.
CONTROL
Place a checkpoint between AI and your data
Every tool an agent calls and every token it spends passes through one checkpoint. You decide what's allowed before anything happens. Sensitive data stays inside the browsers and sessions you already control, and spend stays inside the limits you set.
Approved tools only: MCP traffic gated by identity and validated on every call.
Data stays where it belongs: Clipboard, download, and screen capture controls across browser and virtual sessions.
Spend stays within budget: Token usage metered by person, application, and model, with enforceable quotas.
AI is already running across your organization. Make sure you're the one in control of it.
Citrix. Secure the Work.
MORE TO EXPLORE
Additional resources
Blog
You can’t transform the AI you can’t see
Blog
The adaptive enterprise: Adapting faster than the speed of AI
Blog
The AI governance gap executives can’t ignore — and why it’s about to get worse