What Is Shadow AI & How Could it be Putting your Business at Risk?

September 3, 2025

When AI Tools Fly Under the Radar

Key Takeaways:

Shadow AI is pervasive and poses significant, often unseen, risks to businesses through unauthorized employee use of AI tools that can expose sensitive data and lead to compliance violations.
The risks of shadow AI stem from good intentions, as employees are often unaware that their efforts to be more efficient with readily available AI tools can unintentionally lead to data leaks and serious legal or financial penalties.
Effective management of shadow AI requires guidance, not prohibition, meaning organizations should establish clear policies, provide training, monitor AI activity and create pathways for approved AI tool adoption to mitigate risks while fostering innovation.

Artificial intelligence is everywhere – writing emails, analyzing data, summarizing meetings. Whether you’ve officially adopted it or not, AI is likely already in your business.

In many organizations, employees are quietly using tools like ChatGPT, Google Gemini or GitHub Copilot to streamline their work. Maybe someone used it to debug code, draft a client memo or write a tricky performance review.

Sounds efficient, right?

That’s exactly the problem.

AI is entering businesses through the side door, not through formal IT strategy or approved software rollouts, but one employee at a time. It’s fast, powerful and often invisible to leadership.

This is what’s known as shadow AI, and it represents one of the most pressing and misunderstood technology risks facing businesses today.

What is shadow AI and why should you care?

Shadow AI refers to the use of artificial intelligence tools, models or platforms within an organization without approval, oversight or alignment with IT policies.

It’s the AI-era equivalent of “Shadow IT”, when employees used personal Dropbox accounts or unapproved cloud applications before data policies were updated. However, shadow AI is much more concerning. These tools not only store information; they also consume, analyze and sometimes retain sensitive data, often without any traceable history.

That means an employee who pastes internal pricing models, client communications or product designs into an AI tool could be unintentionally exposing your intellectual property. In highly regulated industries like healthcare, manufacturing or government, the risks extend beyond internal disruption. They may include federal violations, contract loss or legal penalties.

How does shadow AI sneak into your business?

AI tools are popular for one reason: they make life easier. Employees aren’t trying to bypass security. They’re trying to do their jobs more efficiently.

They use AI to save time, simplify tasks or create polished work faster. But most aren’t aware that many generative AI platforms log, learn from and sometimes share the data they receive.

Here are a few examples of how shadow AI is already creeping into different industries:

In healthcare, a clinic manager pastes patient notes into ChatGPT to generate plain-language summaries for discharge paperwork. It’s done to improve communication, but the employee may have unknowingly violated HIPAA by submitting protected health information (PHI) to a public tool.
In manufacturing, an operations manager uploads supplier spreadsheets into a free AI platform to identify cost-saving opportunities. The documents contain confidential pricing and part numbers tied to defense contracts. This could trigger a violation of ITAR (International Traffic in Arms Regulations) and jeopardize critical business relationships.
In local government, a city employee uses an unsecured personal laptop to access a browser-based AI tool to help draft policy memos. The device is later compromised by malware, exposing sensitive city data because the AI tool wasn’t covered under existing endpoint protections.

These examples are not the result of sabotage. They come from people trying to be helpful and resourceful. But good intentions don’t ensure security or compliance. That’s what makes shadow AI so dangerous. It often doesn’t look like a threat until it’s too late.

The Risks of Shadow AI

Ignoring shadow AI won’t make it go away. If anything, the longer it goes unaddressed, the more risks it introduces:

Data leaks: Public AI platforms may retain and learn from employee inputs, which could include proprietary or confidential data.
Compliance violations: Unauthorized AI use may violate HIPAA, GDPR, ITAR or CMMC, depending on your industry and data types.
Intellectual property exposure: Work created or modified with public AI tools may have unclear ownership, which complicates IP protection and enforcement.
Security gaps: AI tools used outside of IT’s purview bypass monitoring and leave endpoints unprotected.
Inconsistent outcomes: Without oversight, teams may use AI tools in conflicting ways, leading to misaligned decisions or inaccurate results.

What you can do Right Now

Banning AI isn’t realistic, nor is it productive. Employees will continue using whatever tools help them work smarter unless given a better option.

The solution isn’t restriction – it’s guidance.

Here’s how to start addressing shadow AI in a meaningful, actionable way:

1. Establish an AI-acceptable use policy

Don’t assume employees know what’s allowed. Define which tools are approved, what data can be shared with them and who is responsible for oversight. When people understand the boundaries, they’re more likely to stay within them.

2. Train and educate your teams

Most employees using AI tools don’t realize they’re creating risk. Offer training tailored to specific departments, use cases and job roles. Help teams understand both the benefits and the boundaries.

3. Monitor and audit AI activity

Leverage tools like data loss prevention (DLP), cloud access security brokers (CASBs) and endpoint monitoring to detect unauthorized AI usage. Visibility is key. If you can’t see it, you can’t manage it.

4. Support innovation within a clear framework

Provide a simple, accessible process for employees to request approval for new AI tools. When it’s too hard to innovate within the system, they’ll innovate outside of it. Make it easier for them to bring AI into the fold responsibly.

For regulated industries, the cost of ignoring AI is even higher

Some industries face more than just financial or operational risk from shadow AI. They face disqualification from key business opportunities.

In government contracting

Under the Cybersecurity Maturity Model Certification (CMMC) 2.0, contractors handling Controlled Unclassified Information (CUI) must follow strict controls around data access and usage. Unauthorized use of public AI tools may violate access control and system integrity requirements, making contractors ineligible for Department of Defense work.

In public agencies

Executive Order 14110, signed in October 2023, directs federal agencies to manage and mitigate AI risk proactively. As public-sector expectations evolve, government vendors will face tighter scrutiny around the tools they use—including how and where AI fits in.

In healthcare

HIPAA violations resulting from AI use can cost thousands of dollars per incident and severely damage patient trust. Tools that analyze PHI must be explicitly authorized and covered by appropriate business associate agreements. Shadow AI tools are almost never compliant.

Lead AI Before it Leads you

Artificial intelligence is not going away. And there are many benefits of using AI in your business. But how you manage it will determine whether it becomes a strength or a liability.

Shadow AI is a sign that your employees are eager to innovate. Rather than punish that behavior, create a path forward that helps them do it safely. Clear policies, open communication and proactive oversight can reduce risk while keeping your business competitive.

This isn’t a tech issue – it’s a leadership issue. The organizations that thrive in the AI era will be the ones who build trust, accountability and alignment into every tool they use.