Disrupt With AI. Defend Against Risk.

Where are you in your AI adoption journey?

The AI Journey diagram. See how Netskope can help you disrupt with AI and defend against risk

1. Experimentation

This initial stage is characterized by an explosion of experimentation with AI tools like ChatGPT and other AI-enabled SaaS applications. Users are focused on accelerating productivity and trying new things.

A significant challenge in this phase is the emergence of shadow AI usage, where employees use unapproved AI tools without company oversight, introducing new risks.

2. Integrated AI in SaaS platforms

In this stage, organizations recognize the need for visibility into AI-enabled interactions as more SaaS applications integrate AI.

The primary focus is on evaluating the security and risk of these applications. This is a crucial step to understand what AI tools are being used and to begin assessing their potential risks.

3. Managed stand-alone AI apps

This is the stage where many organizations currently find themselves. They are standardizing on a single genAI tool (e.g., Microsoft Copilot, Google Gemini) to establish a proper risk posture and create uniform policies. The goal is to mitigate the expanding risk surface by centralizing AI usage and control.

4. Private AI apps

Moving beyond off-the-shelf tools, organizations in this stage build their own AI applications on local or cloud platforms. This expands the risk surface even further.

Key challenges include ensuring the application itself is secure and not vulnerable to exploits, as well as verifying that the data used to train the model is not sensitive.

5. Autonomous AI agents

This stage involves the deployment of autonomous AI agents that act as “10X users” with access to various applications and data within the organization’s environment. This phase introduces new challenges related to AI access and data privileges, as these agents operate independently and can interact with sensitive systems and information

A significant challenge in this phase is the emergence of shadow AI usage, where employees use unapproved AI tools without company oversight, introducing new risks.

In this stage, organizations recognize the need for visibility into AI-enabled interactions as more SaaS applications integrate AI.

The primary focus is on evaluating the security and risk of these applications. This is a crucial step to understand what AI tools are being used and to begin assessing their potential risks.

Moving beyond off-the-shelf tools, organizations in this stage build their own AI applications on local or cloud platforms. This expands the risk surface even further.

Key challenges include ensuring the application itself is secure and not vulnerable to exploits, as well as verifying that the data used to train the model is not sensitive.

GenAI workplace adoption hits new highs

+50%

the percentage of increase in employees using genAI platforms in the three months ending May 2025,

Source: Netskope Threat Labs

Ask SME Anything - The AI Adoption Journey

From initial Shadow AI chaos to standardizing tools like Copilot, the AI adoption journey is full of traps. Watch this to learn the critical security challenges at every one of the five phases of AI adoption before you take the next step.

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