With the explosive growth of user-friendly AI, organizations everywhere face a new and pressing risk: Shadow AI, a term referring to the unauthorized use and implementation of any AI tools and systems in an organization beyond your organization’s approval and control knowledge or approval of the organization’s designated AI authority. The Rise of Shadow AI, and Its impact on your organization will be the focus of this first blog.
75%
of employees in 2027 is forecasted to install and use application that are beyond the visibility of their IT departments.
Source: Gartner
90%
of the 67 AI tools, that organizations use on average, are lacking the approval from their IT department.
Source: Prompt Security Inc.
98%
of employees use unsanctioned apps across both shadow AI and shadow IT.
Source: Veronis
In 2025 AI implementation and adoption is accelerating, but unfortunately so is the risk from Shadow AI, with unsanctioned AI operating beyond your organization’s approval and control. Unsupervised AI is not what you want, in many ways these AI’s can be compared to rogue departments in your organization, making decisions without organizations management and leadership approval. Such rough AI potentially putting your organization’s security, compliance, and reputation at stake, or at least at a risk appetite level most organization can not accept.
The rush to implement AI: Move fast, but let’s now NOT break things!
For sound business and economic reasons, many organizations are rushing to implement AI, unfortunately sometimes at the cost of not fully understanding the risks that might be incurred. A recent McKinsey flash survey of more than 100 organizations with more than $50 million in annual revenue found that 91 percent of respondents doubt their organizations are “very prepared” to implement and scale the technology safely and responsibly.
Source: McKinsey
Shadow AI proliferating
Today, AI are accessible on any device and deceptively easy to deploy, empowering individuals and teams to solve problems faster and better – however this too often is done outside the organizations established IT- and governance policies. In addition many organizations are also dealing with another even more fundamental challenge, which is that AI governance is at an immature level, or even nonexistent, which naturally add to the exposure that your organization are exposed to from Shadow AI risks.
Why Shadow AI Spells Trouble
- Security gaps: Unmonitored AI often introduces vulnerabilities, increasing the risk of breaches and unauthorized access.
- Unmanaged risks: Without oversight, you can’t anticipate or respond to misuse, faulty outputs, or unintended behaviors.
- Regulatory Failures: New policies, such as the EU AI Act, require transparent tracking of all AI projects. Shadow AI makes compliance to such policies impossible.
Why AI Governance is also a route to efficient and scalable implementation of AI
Individuals and teams eager to implement AI quickly could be bypassing the organization’s governance processes. While this seems innovative and a way to move faster forward, it creates several pitfalls:
- Integration hurdles: AI solutions built in isolation are notoriously hard to incorporate into core infrastructures and architecture, stalling innovation at scale.
- Security and compliance risks: Non governed AI can be halted or fully stopped by organizational function, such as legal, compliance or other security functions, for breaching regulatory obligations for introducing security and safety vulnerabilities.
- Fragmented risk profile: Without centralized AI oversight, organizations lose visibility, increasing the chance of lack of transparency, bias and ethical violations.
- ROI limitation: Even the best AI in silos rarely delivers huge enterprise-wide value. Potentially failed integration undermines ROI and thereby maybe also future AI investment appetite.
The crucial factor isn’t about developing and using AI, but much more about how we implement, control, and manage the AI we use. We need to ensure AI is used responsibly to prevent harm to individuals, our environment, and society.
How to tackle Shadow AI: AI Risk Management
- Establish foundational AI Governance practices:
Define standards, procedures, and accountability company-wide—without slowing innovation. Start with practical, actionable guidelines, and scale from there.
- Establish an AI Governance center of Excellence:
Centralize expertise and operational oversight to drive consistency and proactively identify rogue or risky AI activity.
- Enterprise-wide application:
Extend AI Governance to cover every organizational department, product and function. Remember that Shadow AI most often lurks in overlooked areas.
- Centralized AI registration and oversight:
Registre and track all AI projects (internal developed and all solutions with third-party AI embedded). This enables “human in the loop” controls and rapid risk mitigation within your organization. With the number of AI in production and new types of AI, like Agentic AI and Autonomous Agentic AI, you must focus on implementing “human on top” real-time AI Governance monitoring.
- Tech. infrastructure / platform that supports continuous monitoring and management of AI:
Managing AI risks and uncovering Shadow AI is only possible with a strong underlying technology infrastructure / platform for continuous monitoring and risk management of your AI. Manual approaches are simply outpaced by today’s rapid AI development and most likely also with your organization’s appetite to scale AI across the full enterprise.
How 2021.AI helps you fight Shadow AI
At 2021.AI, we empower organizations to confront Shadow AI head-on. 2021.AI enables you to:
- Register and monitor all AI systems in one place
- Operationalize human-in-the-loop and human-at-the-top controls
- Ensure continuous compliance, security, and accountability
- Easily scale robust AI governance as your AI ambitions grow
Don’t let unsanctioned AI undermine your strategy or expose you to risk.
