Shadow AI: The Unseen Risk and Opportunity Inside Your Business

Employees are using generative AI tools under the radar. Here’s why that’s both a security concern — and a signal for change

By: Christopher Pile

You might have heard the term Shadow IT before but have you heard of Shadow AI? Employees across the globe, eager for efficiency and use some shiny new tools, are embracing generative AI but they’re doing it under the radar.

According to the latest Netscope Cloud Threat Report 2025, 72% of users accessing generative AI tools at work are doing so via personal accounts. They’re not waiting for company approved tools. They’re moving fast, using whatever they can to get the job done.

Employees are turning to public LLMs (Large Language Models) to draft documents, summarize reports, generate code, and brainstorm ideas. These tools offer huge gains in productivity. But when sensitive business data is input into public platforms, often with little to no guardrails, it can quickly become a data governance nightmare.

Without the proper controls in place, organisations face:

• Data leakage through public model training
• Compliance breaches by bypassing company data-sharing policies
• Loss of IP through untracked use of proprietary content

Most employees aren’t being malicious, they’re just being resourceful.

Rather than locking access down, forward thinking organisations should see this trend for what it really is: an opportunity to accelerate growth and efficiency.

Employees want better tools. They want to work smarter. They’re showing us where the friction lies. And that opens the door for a smarter, safer approach.

So what should a company do to evolve from Shadow AI to Strategic AI?

1. Invest in Local, Domain-Specific Models
   Rather than relying on public tools, companies can deploy smaller, fine-tuned models hosted securely on private infrastructure. These models offer many of the benefits of LLMs without the data exposure risks.
2. Educate, Don’t Just Restrict
   Build AI literacy across the organisation. Help teams understand not just what tools are available, but how to use them responsibly. Create clear guidelines around data sensitivity, acceptable use, and innovation.
3. Supercharge with the Right Tools
   Instead of blocking tools, offer alternatives. Provide approved AI platforms that integrate into daily workflows — whether it’s an internal chatbot, AI enhanced CRM, or an LLM trained on company-specific knowledge.
4. Create Guardrails That Encourage Use, Not Avoidance
   Strong governance doesn’t mean locking everything down. It means creating safe zones for experimentation, monitoring use, and adapting policies as the technology evolves.

Shadow AI is already in your organisation. The choice is whether to ignore it, resist it, or embrace and channel it.

The companies that win in this new era will be those who don’t just control AI, they collaborate with it. By embracing secure, ethical, and empowering approaches to AI adoption, businesses can turn a risk into their next competitive advantage.