What Is Shadow AI and how to govern it effectively
Most organisations have spent the last decade getting comfortable with the cloud. They’ve invested in Microsoft 365, and moved workloads into Azure. They’ve implemented security controls, identity management, access policies and governance frameworks. They’ve spent years improving visibility into where company data lives and who has access to it.
Then AI arrived. Not with a formal project plan or an executive mandate, but through individual employees looking for faster ways to work. ChatGPT improved an email. Microsoft Copilot summarised a meeting. A spreadsheet was uploaded to analyse trends. An enabled AI assistant suddenly appeared inside a business application. And with this AI moved from a pilot programme or proof of concept to part of everyday work. Sound familiar?
Welcome to the era of shadow AI. It has become quite a challenge hasn’t it? Not because AI is inherently dangerous, but because many organisations have little visibility into how it’s actually being used.
Shadow AI is the use of artificial intelligence tools, assistants, agents and AI-enabled applications without formal oversight, governance or visibility.
If that sounds familiar, it’s because we’ve seen this before. A decade ago, organisations were dealing with shadow IT. Employees signed up for cloud applications without involving IT teams because those tools helped them get their jobs done faster. Today, shadow AI is following the same pattern.
But the difference is that AI doesn’t just store information, it interacts with it, analyses it, transforms it. Sometimes it generates entirely new content from it. In many cases, it requires employees to share information with external AI platforms in order to receive value in return. Shadow AI is emerging as a key governance and security concern because organisations often have limited visibility into which AI tools are being used and what information is being shared.
This is rarely about malicious behaviour. It’s about productivity. People are adopting AI because it works.
Why Shadow AI Is Different From Shadow IT
Traditional shadow IT was usually easy to spot. Someone might’ve purchased a SaaS tool outside procurement processes, or a department may have implemented a project management platform without IT approval. Maybe a team shared files through an unauthorised storage platform. The risks were real, but relatively visible.
Shadow AI is different because it’s both easier to access and harder to detect. Employees no longer need to sign up for a brand-new platform as AI capabilities already exist inside many of the applications they use every day. They’re embedded into browsers, productivity suites, CRM systems, note-taking tools, coding platforms and search engines.
In many cases, users may not even realise they’re interacting with an AI-powered feature, and as a result, organisations are no longer wondering which applications their employees are using but what data is being shared with AI systems. That’s a much more difficult question to answer.
The Real Risk Isn’t The Tool
When people talk about AI risk, discussions often focus on the platforms themselves and if they’re secure. That is of course important, but it can distract from the bigger issue. The real risk isn’t necessarily the tool. It’s the information being shared with it.
Consider these everyday scenarios:
- A salesperson pastes confidential pricing information into an AI assistant to draft a proposal
- A finance employee uploads budget forecasts to create an executive summary
- A developer asks an AI platform to troubleshoot code containing proprietary intellectual property
- An HR manager uses AI to help rewrite a performance review containing personal employee information
None of these actions are malicious. In fact, they’re exactly the kinds of tasks AI is excellent at helping with. But they’re also situations where sensitive information could leave organisational boundaries in seconds if appropriate controls don’t exist. AI-driven productivity often arrives before governance, leaving employees to make risk decisions for themselves.
The Visibility Problem
The biggest challenge with shadow AI isn’t that employees are using AI. Organisations are now challenged with not knowing where, when or how employees are using AI.
Can you confidently answer any of these questions?
- How many AI tools are currently being used across your organisation?
- Which departments are using them most heavily?
- What types of information are being entered into those platforms?
- Which AI tools have been formally approved?
- Which ones have appeared without anyone’s knowledge?
Without knowing which AI tools are being used, what information is being shared, or where information is ultimately being processed you have a visibility issue. And without visibility it’s impossible to govern.
Why Banning AI Doesn’t Work
When leadership discovers shadow AI, the first instinct is often to block it, but unfortunately, that rarely solves the problem.
Employees use AI because it helps them complete work faster, improve quality and eliminate repetitive tasks. Removing that capability doesn’t remove the demand, it simply pushes usage elsewhere.
We’ve already seen this dynamic with cloud applications, file-sharing platforms and personal devices. When people need a tool to do their jobs more efficiently, they’ll often find one. So AI doesn’t disappear, it simply becomes less visible, and almost always riskier.
The organisations managing AI most successfully aren’t those saying “no.” They’re the ones creating environments where it’s safe to say “yes.”
What Good AI Governance Looks Like
The best AI governance programmes are designed to enable AI safely. That starts with accepting a simple reality – AI use is already happening. Once organisations accept this, governance becomes significantly easier.
A practical approach generally involves four steps:
1. Create Visibility
You can’t govern what you can’t see. Understanding which AI tools, assistants, browser extensions and AI-enabled platforms are being used is the foundation of any governance strategy.
2. Understand Data Exposure
Different information carries different levels of risk. Public marketing content isn’t the same as customer records. A product brochure isn’t the same as source code. A mature governance programme understands these distinctions and applies appropriate controls.
3. Provide Clear Guardrails
Most employees want to do the right thing. They simply need guidance.
- Which tools are approved?
- What data can be used?
- What data must never be shared?
- Where does human oversight remain essential?
Clear answers make safe behaviour easier.
4. Monitor And Adapt
AI is evolving too quickly for static policies. Governance needs to evolve alongside technology, user behaviour and emerging business requirements.
The Future Of Cloud Governance Includes AI Governance
Cloud governance used to focus primarily on applications, users and infrastructure. Today, another layer has emerged – AI.
It’s becoming embedded into almost every modern platform and influencing business decisions. It’s interacting directly with organisational data. And soon, AI agents will be taking increasingly autonomous actions on behalf of users and businesses.
That means organisations need to stop viewing AI as a standalone initiative as it’s becoming part of the cloud environment itself. The same disciplines that apply to cloud governance now need to extend to AI governance as well. The businesses that embrace this reality early will be far better positioned than those waiting for problems to emerge first.
From Shadow AI To Governed AI
The goal isn’t to eliminate AI usage. Nor is it to blindly trust it. The goal is visibility.
Once you have visibility, you can create policies, apply controls, and educate staff. You can identify risks before they become incidents, and most importantly, you can enable innovation without sacrificing governance. That’s the opportunity.
How Prompt AI Helps Bring Shadow AI Into The Light
First off, understand where AI is already being used.
Prompt AI from SentinelOne is designed to help organisations discover AI usage across the business, identify shadow AI activity, understand how employees are interacting with AI platforms, and apply practical governance controls that reduce the risk of sensitive information being exposed. It provides organisations with greater visibility, governance and control over workplace AI use, including both approved and shadow AI activity.
Rather than forcing organisations to choose between innovation and control, Prompt AI helps create a middle ground where employees can continue benefiting from AI while governance teams gain the oversight they need. It supports practical guardrails, protection of sensitive information and governance of emerging AI applications and agents.
The organisations that gain the greatest value from AI will be the ones that understand it, govern it and use it confidently.
Want to understand how much shadow AI already exists in your organisation?
Learn how Advantage and SentinelOne Prompt AI can help you identify, govern and secure workplace AI usage. Explore Prompt AI.
