Netskope AI Security · resource

Securing the AI era.

Protect every way your business touches AI. From shadow chatbots to autonomous agents, Netskope One AI Security gives you a single platform to see, understand and control your entire AI ecosystem, without slowing innovation down.

The challenge

A dual mandate: unlock AI, and defend against it.

Boards are telling IT leaders to embrace AI and cut costs, and to act as gatekeepers against data leaks, all at once. Getting it right starts with understanding exactly where the risk lives.

Enable innovation

Let teams build with AI

Experiment, adopt and build with AI to drive real, measurable business value, fast.

Control the risk

Defend data & reputation

Protect data, reputation and compliance against leaks, misuse and AI-native attacks, without blocking progress.

The adoption curve

Five stages of AI adoption. Five new risks.

Every organisation sits somewhere on this curve, usually on several rungs at once. Click each stage.

Risk · Shadow AI

Invisible data exposure

Employees paste sensitive data into personal chatbots that security teams can’t see or govern. 72% of enterprise users still reach genAI through personal accounts at work.

Risk · Silent data sharing

SaaS switches AI on by default

Trusted apps enable AI features automatically. An AI notetaker quietly records and stores company-confidential information, with no one deciding it should.

Risk · Internal leakage

Over-permissioned corporate AI

A corporate AI assistant surfaces files a user was never meant to access, leaking sensitive data inside the organisation, exactly the Copilot problem.

Risk · Model weakness

Custom models inherit flaws

Custom and open-source models carry vulnerabilities: prompt injection, jailbreaks, and biased or harmful output, often shipped untested.

Risk · Non-human blind spot

Agents act without oversight

Autonomous agents act over APIs and the Model Context Protocol, machine-to-machine, bypassing human-centric security and risking data exfiltration.

State of AI security · 2026

Adoption is racing. Governance isn’t keeping up.

A survey of 1,253 security professionals found the same pattern almost everywhere: AI is being deployed at production speed on a security foundation that barely exists. The good news, the gaps are now measurable, which means they’re fixable.

94%

lack complete visibility into AI usage

88%

can’t tell a personal AI account from a corporate one

92%

have no confirmed way to catch data once AI rewrites it

91%

can’t stop a risky AI action before it executes

Source: Cybersecurity Insiders, 2026 AI Risk and Readiness Report

Why it’s hard

The tools you trust weren’t built for AI.

AI doesn’t just add new apps, it adds new behaviours. Legacy proxies and firewalls can’t read intent inside a prompt, can’t see agent traffic, and can’t tell a safe AI conversation from a dangerous one.

You can’t secure what you can’t see

Unmanaged tools, personal accounts and AI quietly embedded in everyday SaaS sit outside the security team’s view, until exposure has already happened.

New threats traditional tools miss

Prompt injection and jailbreaks are AI-native attacks. A firewall sees an allowed connection; it has no idea the prompt inside is trying to trick the model into leaking secrets.

Agents act without oversight

Autonomous agents talk machine-to-machine over APIs and MCP. Without a checkpoint, they risk credential leaks, tool poisoning and unauthorised exfiltration.

The "transformation test" · why old DLP goes blind
Original · DLP catches it

"Launch date for Project Titan is March 3. Budget $4.2M, codename Titan."

✓ Keywords & patterns match → blocked
AI rewrites it · DLP misses it

"Our upcoming strategic initiative kicks off early spring with a multi-million investment."

✗ No pattern match → sails through

Pattern-based DLP matches character strings; AI transforms meaning while keeping the secret intact. The fix is inspection that reads intent, not just keywords.

The solution

One checkpoint in the path of every AI conversation.

Think of Netskope One as a smart checkpoint sitting between the people and agents using AI and the models they talk to. Every prompt and response passes through, so it can be seen, inspected and controlled in real time.

Inbound

Prompts & requests

Inspected for sensitive data, injection and misuse before they reach the model.

Inspection

Zero Trust Engine

Integrated DLP and threat protection read intent, for both human and agent traffic.

Outbound

Responses & data

Unsafe content, code and data leaks filtered out of the reply.

The products

Every risk has a matching control.

Each product maps directly to a risk on the adoption curve, and they share a single platform, console and policy engine. Buy one, several, or all.

Find out where your AI risk really lives.

Netskope AI protection

Visibility and control across every AI tool your people use.

From Copilot to public AI, inline.

What does Netskope AI protection do?

Sits inline between users and AI apps (Copilot, ChatGPT, Gemini, Claude and others), applies DLP to prompts and uploads, blocks risky use, and gives full visibility of AI activity across your organisation.

Does it cover Microsoft 365 Copilot?

Yes. Inline visibility and DLP for sanctioned AI (Copilot) and unsanctioned AI (public ChatGPT, Gemini).

What about company-built AI agents?

Netskope can apply DLP and policy to API-based AI calls as well as user-facing apps.

How does it fit with Cyera DSPM?

Cyera shows where sensitive data lives so you can fix permissions before AI surfaces it. Netskope controls what AI can do with that data in motion. They feed each other.

Does it slow down the user AI experience?

No noticeable impact. Inline inspection is real-time.

How do we start?

See our AI security page or book an AI Readiness assessment.