Shadow AI and Insider Risks: A Quiet Crisis in the Making

Rajesh Aravind M

Artificial Intelligence is quickly becoming a staple in modern organizations. Teams

are experimenting with generative tools to simplify tasks, improve productivity, and

deliver faster outcomes. But as with any powerful technology, there is a flipside—one that many organizations are only now beginning to realize.

Shadow AI—the unauthorized or unmonitored use of AI tools within

organizations—is fast emerging as a significant risk, especially when coupled with

insider activity. If left unaddressed, this could evolve into a serious security blind

spot.

Understanding Shadow AI

Shadow AI refers to the unsanctioned use of AI models, applications, or platforms by

employees or departments without IT or cybersecurity team oversight. This can

include anything from using ChatGPT for writing code or drafting documents, to

uploading sensitive data into translation or image-generation tools for faster

processing.

Often, it stems from good intentions—employees trying to be more efficient or solve

problems independently. But the risks are far from trivial.

Why It Matters: Insider Risk Amplified

Most insider threats aren’t malicious—they’re unintentional. Shadow AI fits squarely

in that category. When employees use AI tools without understanding how they

handle data, they may unknowingly expose intellectual property, customer

information, or sensitive internal documents to third-party systems.

The result? Data leakage, regulatory non-compliance, or even reputational damage.

Some real concerns include:

• Untracked data leaving the perimeter: Employees pasting confidential

content into AI tools hosted externally.

• IP ownership issues: Code or designs fed into generative platforms could be

reused or retained in training datasets.

• AI hallucinations leading to flawed decisions: When AI-generated output

is taken at face value without verification.

• Jurisdictional challenges: AI tools often process data in data centers across

multiple countries—creating privacy compliance gaps (especially under

regulations like DPDPA, GDPR, or HIPAA).

The Risk Is Already Among Us

Research and anecdotal evidence suggest Shadow AI is already present in most

mid-to-large organizations. Employees in marketing, HR, product design, and even

legal teams are experimenting with AI to simplify daily work—often without realizing

the risks. The key issue is this: lack of visibility and governance. If security and compliance teams don’t even know AI tools are being used, how can they secure them?

What Can Be Done?

Tackling Shadow AI isn’t just a tech problem—it requires cultural, procedural, and

strategic change. Here’s a practical approach for leaders:

1. Baseline the Usage

• Start by identifying where and how AI tools are being used. Use monitoring

tools to detect access patterns and survey employees across departments.

2. Establish Usage Policies

• Draft and roll out a clear AI usage policy. It should define acceptable uses, red

lines, and approval workflows for adopting new AI platforms.

3. Awareness and Enablement

• Educate employees on the risks, not just the rules. Most employees don’t

want to put the company at risk—they just need guidance on how to use AI

safely.

4. Implement Guardrails

• Leverage data loss prevention (DLP) and cloud access security broker

(CASB) tools to monitor AI usage.

• Introduce access control for sensitive data to prevent it from being exposed

through AI tools.

5. Treat AI Governance as a Strategic Priority

• Establish a cross-functional team to oversee AI adoption across the business.

This should include IT, legal, HR, and compliance leaders.

• Align your governance strategy with upcoming standards like the NIST AI Risk

Management Framework and ISO 42001.

Final Thoughts

Shadow AI is not a futuristic threat. It’s already woven into our workplaces—and it’s

growing every day. The challenge lies not in stopping AI adoption, but in managing it

responsibly.

Leaders must create an environment where innovation can thrive—securely and

ethically. By recognizing Shadow AI as a potential insider risk, and acting decisively,

organizations can stay ahead of this quiet crisis before it becomes a headline.