03-09-2026

The Main Silent Challenge for Corporate Governance

Shadow AI (or unauthorized Artificial Intelligence) has become one of the most complex operational and security risks for technology and regulatory compliance teams. Unlike traditional perimeter threats, this phenomenon operates in a completely decentralized and often imperceptible manner. While IT departments allocate resources to securing official infrastructure, organizations are facing a massive and parallel adoption of non-approved technology solutions, driven by teams seeking to optimize their day-to-day productivity without fully understanding the information security implications,

The Corporate Technology Iceberg

When we think about a company’s systems, we tend to imagine an orderly structure: software evaluated and approved by the IT Department, authorized corporate emails, official networks and devices, servers, and document repositories. That’s the tip of the iceberg, the part we can see..

Shadow AI is the submerged foundation: applications, browser extensions, web-based image generation platforms, automated translators, and coding assistants that employees adopt on their own, using free or personal accounts. These tools do not go through the organization's IT security review process, are not covered by confidentiality agreements with the provider, and operate within an internal legal and governance vacuum .

Why Is This Phenomenon Happening on Such a Massive Scale?

It is not driven by rebellion, but by a speed gap .

• The urgency of day-to-day work: while evaluating, approving, and deploying an official AI tool within a company can take considerable time due to rigorous compliance and security processes, any employee can go online, sign up  for a modern AI platform for free, and start using it immediately.

   

• The technological gap: Many employees discover that today’s artificial intelligence far outperforms legacy systems (the outdated software programs and IT platforms that companies continue to maintain largely out of tradition). Because these external tools can dramatically increase their productivity, employees often prefer using them rather than being tied to official corporate software .

   

• The disconnect between senior management and the tools used by employees: Middle managers and executives often approve strict technology-restriction policies from a purely theoretical perspective, without understanding the real friction involved in day-to-day operational work.  When there are no formal channels through which teams can communicate their actual automation needs, the only perceived alternative is to operate outside official guidelines.

   

The Real Risks (Beyond Simply Pasting Sensitive Data)

Although confidential data leakage is the most obvious danger, Shadow AI creates several other significant operational risks:

• Loss of intellectual property: Under the terms of service of many free platforms, uploaded content may be used as part of model training. If a programmer uploads proprietary source code or a designer uploads an unreleased product sketch, that intellectual property becomes exposed.

   

• The skills obsolescence trap: When staff systematically delegate writing, analysis, critical thinking, or problem-solving tasks to AI without meaningful human oversight, teams may gradually lose professional skills. Excessive reliance can erode independent judgment and leave employees vulnerable when a tool fails or produces subtle errors.

   

• Hallucinations and corporate errors: If an employee uses an unverified AI to make a business decision, analyze metrics, or draft contractual clauses, and the tool “hallucinates” (confidently generating an incorrect or fabricated fact ), the company could face financial losses or legal consequences.

   

Some Examples:

• An employee pastes a payroll file into ChatGPT.
• A lawyer copies a client's contract into an AI tool to have it summarized.
• A developer pastes source code from an internal application into an AI tool for debugging. .
• An employee uploads month-end financial closing information to a public AI platform .

All of these situations could potentially expose::

• Personal data.
• Financial information.
• Intellectual property.
• Client information.
• Information protected by confidentiality agreements.

   

How Are Smart Companies Managing This?

Organizations that are managing these issues most effectively have understood that banning the technology does not work.

Instead, the current approach is increasingly based on three pillars:

• Creating safe zones: Purchasing corporate licenses for reliable tools (such as enterprise versions of ChatGPT, Copilot, or other platforms) where company data is protected by contract and is not used to train public models.

• Fear-free education: Clearly explaining why certain tools pose a risk, while giving employees clear alternatives instead of simply telling them “you can’t use this.”

   

• Listening to users: When teams request the incorporation of new AI tools, the key is to open channels of dialogue. Rather than banning a proposed technology, organizations can assess it and, if it passes internal security requirements, officially integrate it so everyone can benefit from it safely..

Conclusion:

The key to today’s balance is no longer blocking innovation that comes from the front lines, but channeling it so that it adds value without putting the company at risk.

Technology is a powerful ally, but the intelligent and responsible use of these tools ultimately depends entirely on us.

IT
September 2026

This newsletter has been prepared by Jebsen & Co. for the information of clients and friends. Although it has been prepared with the greatest care and professional zeal, Jebsen & Co. does not assume responsibility for any inaccuracies that this bulletin may present.