What is shadow IT?

Shadow IT is the use of software, hardware, cloud services, or other technology inside an organization without the knowledge or approval of the IT department. It usually appears in one of two ways: an employee adopts an unapproved tool to handle work data, or uses an approved tool in an unauthorized way, such as through a personal account. The intent is rarely malicious. People reach for whatever helps them get the job done. But because IT has no visibility into these tools, it cannot secure, monitor, or maintain them, and that blind spot is where the risk lives. Shadow IT has grown with the shift to cloud and software-as-a-service (SaaS), where a new tool is a sign-up away, and it has accelerated again with generative AI. This page covers what shadow IT is, why it happens, the risks and the genuine upsides, common examples including the fast-rising category of shadow AI, and how organizations bring it back under control.

Key takeaways

Shadow IT is unsanctioned technology. It is any hardware, software, or service used for work without IT's approval or awareness.
It is usually well-intentioned. Most shadow IT comes from employees trying to work faster or better, not from anyone acting maliciously.
The core problem is lost visibility. IT cannot protect what it cannot see, so shadow IT creates gaps in security, monitoring, and compliance.
It carries real benefits too. Shadow IT can surface better tools and drive productivity, and a share of it eventually becomes officially approved.
Shadow AI is the fastest-growing form. Unsanctioned use of generative AI tools adds new data-leakage and compliance risks on top of traditional shadow IT.

Why shadow IT happens

Understanding the motive is the first step to managing it, because shadow IT is a symptom more than a cause. The common drivers:

Approved tools fall short. The sanctioned option may be slower, clunkier, or missing a feature, so employees pick something that fits the task better.
People are unaware of the risk. Many do not realize that using a personal app for work data can expose sensitive information, so they are not deliberately breaking the rules.
SaaS and cloud make it effortless. A new service can be running in minutes with a credit card or a free tier, with no procurement step to slow it down.
Buying happens outside IT. When departments fund their own tools, IT is often out of the loop, and industry surveys have found a large share of technology spending now happens outside the IT budget.
Remote work and BYOD blur the line. Personal devices and home networks mix work and personal tools in ways that are hard for IT to see or control.

Common examples of shadow IT

Shadow IT takes many forms, from a single file transfer to a whole department running an unsanctioned platform. Typical examples include:

Unapproved SaaS and cloud storage, such as sharing corporate files through a personal Dropbox, Google Drive, or messaging app.
Personal devices (BYOD), including phones, laptops, and USB drives used to access or move work data outside managed controls.
Unvetted productivity and collaboration apps, like project or note tools adopted by a team on personal accounts.
Software installed without IT vetting, including browser extensions that can quietly read or move data.
Generative AI tools, covered below as shadow AI, which have become one of the most common new forms.

The scale is easy to underestimate. Studies have repeatedly found that the great majority of employees use some software their IT team has not cleared, and that organizations typically run far more cloud services than they can account for. The precise figures vary by study, but the pattern is consistent: most environments contain more shadow IT than their owners think.

Risks and benefits of shadow IT

Shadow IT is not purely negative, which is part of what makes it hard to manage. The same behavior that creates exposure can also surface genuine value. Weighing both sides matters.

Risks	Benefits
Data exposure and breaches: Sensitive data lands in tools IT cannot secure or monitor.	Productivity: The team closest to the work often finds the tool that fits it best.
Compliance violations: Unmanaged handling of data can breach regulations such as GDPR.	Innovation: Employees test and validate useful tools before formal adoption.
Lost visibility: No logging or oversight means attacks on shadow tools can go unnoticed.	Highlighting gaps: Shadow IT reveals where approved tooling is falling short.
Wider attack surface: Unmanaged apps and devices bypass endpoint, DLP, and MDM controls.	Path to sanctioned tools: A portion of shadow IT is later vetted and formally approved.

The balance tips toward risk as shadow IT scales. A single team using one unsanctioned app is manageable; hundreds of unknown services across an organization is a serious exposure. The goal is not to pretend the benefits do not exist, but to capture them through sanctioned channels instead of unmonitored ones.

Shadow AI: The newest form

Shadow AI is the unsanctioned use of artificial intelligence tools, most often generative AI assistants, without IT oversight. It is a subset of shadow IT, and it is growing quickly because the tools are so accessible and so useful. The distinction matters because shadow AI adds risks specific to how AI handles data. An employee pasting confidential text, source code, or customer data into a public AI tool may be sending that information to an external service with no guarantee of how it is stored or used, which raises fresh data-protection and intellectual-property concerns on top of the usual shadow IT exposure. The lesson from shadow IT applies directly: blanket bans tend to fail, while clear guidance, approved AI options, and role-based permissions channel the demand safely.

How to manage shadow IT

Managing shadow IT is a mix of technology, process, and culture. Enforcement alone does not work, because it pushes the behavior further underground. A workable approach combines a few elements:

Discover what is actually in use. Shadow IT discovery tools identify the approved and unapproved systems and services across the environment, so IT can see the true picture before deciding what to allow, restrict, or block.
Use dedicated controls where they fit. A cloud access security broker (CASB) adds visibility and control over cloud apps, bundling discovery, access control, and data loss prevention (DLP); SaaS security posture management (SSPM) helps govern sanctioned SaaS configurations.
Set a clear, realistic policy. A shadow IT policy defines how new tools are requested, approved, and managed, and it works best when it is easy to follow rather than purely restrictive.
Offer good approved alternatives fast. Much shadow IT disappears when the sanctioned option is genuinely good and easy to get, so a quick, low-friction approval path removes the incentive to go around IT.
Train people and drop the blame. Explain the risks in concrete terms, and pair it with a no-blame culture so employees disclose the tools they use instead of hiding them.

Expert insight: you cannot defend what you cannot see

Every account of shadow IT circles back to the same word: visibility. The reason shadow IT is dangerous is not that a given SaaS app is inherently unsafe, it is that the security team does not know the app exists, so it sits outside monitoring, patching, and incident response. An asset nobody is tracking is an asset nobody is defending. When a threat actor compromises an unmanaged app or device, the first sign of trouble is often the breach itself.

This is where the discovery side of shadow IT meets security operations. Knowing your real attack surface, every asset, service, and account that touches the organization, is the precondition for defending it, and it is exactly what shadow IT erodes. Sekoia is a European cybersecurity vendor whose platform includes cyber asset attack surface management (CAASM) through Sekoia Reveal, which builds an inventory of an organization's assets and helps surface the unknown or unmanaged ones that shadow IT creates. Feeding that asset picture into the wider SOC platform means that when a previously invisible service starts behaving oddly, it can be seen and investigated rather than missed.

To be clear about scope, dedicated shadow IT governance, blocking a specific SaaS app, enforcing DLP on it, managing its configuration, is the job of tools like a CASB or SSPM, and Sekoia is not one of those. What a unified AI SOC platform with asset visibility adds is the security half of the problem: reducing the blind spots that shadow IT creates, and detecting malicious activity on assets that governance tools alone would never watch. As a European vendor with a data-sovereignty posture, Sekoia also fits organizations that need asset and security data handled under European governance.