For years, cybersecurity strategies have largely focused on external threats: ransomware, phishing, vulnerability exploitation or supply chain attacks.
However, there is a risk that continues to grow inside organisations, often without malicious intent, without visible alerts and without going through normal security processes.
That risk is called Shadow IT and, more recently, Shadow AI.
Shadow IT: An Old Problem That Never Went Away
Shadow IT is not a new concept. It refers to the use of applications, platforms, cloud services or technological tools without the knowledge, validation or control of IT and Security teams.
In most cases, it does not arise from an intention to bypass rules, but from the need for business agility, productivity or autonomy. Typically, something that is used or installed temporarily eventually becomes permanent.
The problem with these tools and solutions is that they operate outside normal governance mechanisms:
- without risk assessment
- without security validation
- without access controls
- without adequate monitoring
- without visibility into how data is handled
For many years, this phenomenon was mainly associated with cloud platforms, SaaS applications and external storage solutions, but today the problem has taken on a new dimension.
Shadow AI in Organisations: The New Invisible Layer of Digital Risk
The widespread adoption of generative artificial intelligence tools has created a natural evolution of Shadow IT: Shadow AI.
In this case, the risk is not limited to the use of unauthorised software. It also involves the use of AI models, automations or generative tools outside organisational policies and processes, in short, without governance.
The growth of this phenomenon is particularly difficult to control because adoption is extremely fast and often invisible to security teams.
Unlike traditional Shadow IT, many AI capabilities are already embedded into everyday applications, including productivity suites, collaboration platforms, development tools, CRM systems and cloud platforms.
This context makes the use of AI easy to overlook.
Shadow AI and Data Protection: Where the Real Risk Lies
One of the most common mistakes is reducing Shadow AI to a simple issue of using unapproved tools.
In reality, the real problem lies in the data that is being entered into these systems.
Many organisations still have little or no visibility into:
- what information is being entered into public models
- what data is being processed externally
- which prompts contain sensitive information
- what integrations are connected to internal systems
This creates real risks such as:
- exposure of confidential information
- loss of intellectual property
- regulatory non-compliance
- misuse of personal data
- automated decisions without adequate oversight
The complexity increases because many models operate as black boxes, making auditing, traceability and explainability more difficult.
Shadow AI and Governance: When Adoption Outpaces Control
One of the most critical aspects of Shadow AI is speed.
Teams adopt tools quickly because productivity gains are immediate. The problem is that governance mechanisms, risk assessment processes and policy frameworks rarely evolve at the same pace.
The result is a dangerous disconnect. Technology advances, usage increases, but control remains incomplete.
In many organisations, AI is already part of daily operations long before clear policies exist regarding what can and cannot be used.
Why Blocking Shadow AI Does Not Solve the Problem
Faced with this reality, many organisations attempt to respond through prohibition.
In practice, that rarely works.
When technology addresses real productivity needs, people will always find alternative ways to use it.
The challenge of Shadow AI is not solved simply by blocking access. It requires visibility, governance, clear policies, training and the integration of security into actual business processes.
Without that, the risk simply becomes more invisible.
Shadow AI and Regulation: The Impact Is Growing
The rise of Shadow AI is taking place at a time when regulatory pressure around security, governance and risk management is increasing significantly.
European regulations such as NIS2, DORA, the CRA and the AI Act are raising expectations around topics such as digital risk control, technology governance, data protection, traceability and organisational accountability.
This means that uncontrolled AI usage quickly stops being just a technical issue and becomes a governance and compliance issue as well.
Shadow AI in Organisations: A Governance and Maturity Challenge
Shadow AI highlights the difficulty organisations face in keeping governance models aligned with the speed of digital transformation.
The most mature organisations do not simply try to block technology. They seek to understand how it is being used, identify the real risks, define clear boundaries and create mechanisms for continuous oversight.
The challenge is not to prevent the use of AI, but to ensure it can be used without losing control over risk.
If your organisation is already using generative AI tools but still lacks clear visibility into where the risks lie, the problem may not be the technology itself, but rather the absence of governance over the way it is being used.
At Balwurk, we help organisations identify exposure associated with Shadow IT and Shadow AI, establish control mechanisms and integrate security and governance into the real-world use of these technologies.
