Dean Anderson, Commercial Director.

It’s unlikely that you haven’t heard the term Shadow IT. It has been a security issue for over a decade, after taking off around 2010 as the iPhone and other smartphones started to penetrate the consumer market and became must-have devices everyone carried. Of course, many people getting a new modern experience on these devices outside of work wanted to use them for work-related functions. So they did!

Before going on, we should define what we mean by shadow IT here in 2025. It’s a much broader topic than people using their own smart devices for work activities. The term now encompasses other things, such as using cloud services that the IT department does not sanction. Think of employees using personal email accounts to share files, downloading unsanctioned collaboration apps, or storing data in external cloud drives. Dropbox was a prominent example of this, and it’s now joined by services like iCloud and others. 

Another significant shadow IT use is when whole departments within organisations start using, and often paying for, SaaS cloud services like Slack, Microsoft 365, Google Docs or any of the hundreds of other cloud-based services available. 

Beyond Traditional Shadow IT: The Rise of “Shadow AI”

The concept of Shadow IT has evolved significantly with the advent of generative AI technologies. Data and security specialists identify “Shadow AI” use as a critical risk area. They define it as employee use of AI technologies without necessary approvals or oversight from leadership, IT, or security teams.

In the last two years, people have started to use Generative AI tools like ChatGPT, Dall•E, Claude, CoPilot, Gemini, and others to help them do their jobs. Data from Microsoft shows that 75% of employees were already using AI tools at work in late 2023 and early 2024, often without proper authorisation or oversight. A figure that’s unlikely to have diminished much since. This disconnect between official policy and actual practice creates substantial risks that can compromise an organisation’s security, compliance status, and financial health due to AI and other shadow IT usage!

What makes Shadow AI particularly concerning is its accessibility. AI tools are often web-based, requiring nothing more than a browser to access. This means employees can easily upload sensitive company information to these platforms without understanding the potential consequences.

The Business Risks Are Real—and Potentially Expensive

Shadow IT and Shadow AI are not just operational nuisances. They are genuine business risks with financial and legal consequences.

Data Breaches and Compliance Failures – Unsanctioned tools often lack encryption, access control, and data residency assurances. Employees who copy sensitive data into unvetted AI tools or personal apps may unintentionally breach regulations like GDPR, the EU AI Act, or sector-specific data protection laws. Such breaches can result in fines, lawsuits, and long-term reputational damage.

Intellectual Property Leakage – Employees using generative AI to write proposals or code may inadvertently paste proprietary or client information into tools that store, log, or train new models with that data. This could expose trade secrets, breach NDAs, or create legal grey areas around IP ownership.

Cybersecurity Vulnerabilities – Unauthorised tools create attack surfaces that security teams don’t know exist. Public AI apps and unsanctioned SaaS platforms can introduce vulnerabilities such as prompt injection attacks, malicious scripts, or data exposure to third parties.

Financial Impacts – Even a minor Shadow IT breach can result in:

• Operational downtime
• Lost revenue from service disruption
• Emergency remediation costs
• Loss of client trust and contracts
• Increased cyber insurance premiums or cover denial

Special Considerations for Shadow AI – With generative AI tools specifically, organisations face unique risks:

• Prompt Injections – Employees using AI tools may inadvertently enable malicious actors to manipulate responses.
• Training Data Poisoning – Company information submitted to these systems may be used to train models that are accessible to competitors.
• Data Privacy Violations – Employee use of AI tools may result in sharing customer or employee personal information outside approved channels.
• Hallucination Issues – AI tools can generate convincing but entirely false information that staff might use as factual information.

The stakes are high for high-value, highly regulated industries such as financial services, legal, or healthcare.

Mitigating Shadow IT – What Can Be Done?

Addressing Shadow IT requires a multi-faceted approach that balances security needs with the productivity benefits that often drive employees to seek these solutions:

Develop Comprehensive Acceptable Use Policies (AUPs) – If some Shadow IT usage is inevitable or even beneficial, organisations must govern its use. They should develop and enforce clear AUPs tailored to specific risk areas. Create specific AUPs for different technology categories:

• Generative AI Tools – Clearly outline which AI platforms are approved, what data can be shared, and appropriate use cases. 
• Mobile Devices – Establish expectations for using personal devices for work purposes. 
• Remote Access Solutions – Define approved methods for accessing company resources outside the office. 
• Cloud Services – Specify which services meet company security standards. 

These AUPs should be living documents that get updated as technology evolves, with clear consequences for violations balanced against employee education. And new AUPs should be added as needed.

Implement Technical Controls – You can’t manage what you can’t see. Organisations must deploy advanced monitoring tools to detect Shadow IT usage, particularly AI tools accessed through browsers or non-corporate accounts. This involves real-time scanning, network behaviour analysis, and integration with identity platforms. Implement the following:

• Network Monitoring – Deploy solutions that identify unusual application usage or data transfers.
• Data Loss Prevention (DLP) – Implement tools that prevent sensitive information from leaving approved channels.
• Application Allowlisting – Configure systems to run only approved applications.
• Single Sign-On Solutions – Make accessing approved tools more convenient than alternatives.

Create a Culture of Security Awareness – Shadow IT use often stems from well-intentioned problem-solving. Businesses should run internal awareness campaigns to educate staff about the risks, not just the rules. Employees should feel empowered to report Shadow IT or AI use without fear of punishment. Transparency helps organisations build a culture of security rather than silence. Cultivate an organisation that has:

• Regular Training – Educate employees about the risks associated with Shadow IT.
• Open Communication – Create channels for employees to suggest new tools they find valuable.
• Security Champions Programme – Identify security-minded individuals in each department to promote compliance.
• Positive Reinforcement – Recognise and reward secure behaviour rather than only punishing violations.

Streamline Technology Approval Processes – If staff are turning to unauthorised tools, it often means the approved ones aren’t working for them. IT leaders must take that information seriously and provide fast, usable, and secure alternatives—including sanctioned AI tools like Microsoft 365 Copilot, rolled out with proper guardrails.

• Expedited Evaluation – Create faster assessment pathways for commonly requested tools.
• Proof-of-Concept Trials – Allow controlled testing of new technologies before full deployment.
• User Feedback Loops – Actively solicit input on tool effectiveness and usability.
• Regular Technology Reviews – Periodically assess whether approved solutions still meet business needs.

You Need Expert Support

The risks posed by Shadow IT are too significant to ignore. As technologies evolve and proliferate, organisations that fail to implement appropriate controls face increasing exposure to data breaches, regulatory penalties, and operational disruption.

Tackling Shadow IT and AI use is not a one-off exercise but an ongoing, strategic effort that touches on cybersecurity, compliance, operations, and culture. Most internal teams are already stretched and may not have the expertise or tools to continuously monitor, assess, and manage these hidden threats.

That’s where Cased Dimensions can help. Our experts work with organisations to:

• Audit current Shadow IT and Shadow AI risks.
• Design layered security frameworks aligned with zero-trust principles.
• Build out AUPs that reflect your business model and regulatory obligations.
• Implement detection and response tools to reduce your attack surface.
• Advise on secure AI adoption strategies that balance innovation with control.

Cased Dimensions brings the expertise, technology partnerships, and proven methodologies to help your organisation identify and address Shadow IT risks effectively. Our approach balances security requirements with the need for innovation and productivity, ensuring your technology environment remains secure and competitive.

Contact Cased Dimensions to start a conversation about Shadow IT risk and to discover how our expertise can help protect your organisation’s data, reputation, and bottom line. Our security experts will work with you to develop a tailored approach that addresses your specific needs and challenges. Don’t wait for a security incident. Take proactive steps to ensure your technology environment remains secure, compliant, and efficient.