Shadow AI: The Silent Cyber Risk Every CISO Must Confront in 2025

Introduction

A few years ago at a large tech company, I helped raise awareness about Shadow IT (the use of unapproved apps and tools like Dropbox, Slack, or other SaaS platforms outside official IT channels). Employees embraced them because they made work faster and easier. What they didn’t realize was that these seemingly harmless tools were quietly creating hidden risks, from data breaches to compliance violations waiting to happen.

Fast forward to today, and history is repeating itself. Only now, it’s even more complex and dangerous. Employees are now turning to AI tools to automate tasks, generate code, analyze data, and even make decisions, often without any oversight. This growing phenomenon, known as Shadow AI, potentially poses an even bigger threat.

While data is moved around in Shadow IT, AI tools can potentially transform, expose, and learn from the data. According to the State of the Shadow AI Report, more than 80% of workers, including nearly 90% of security professionals, use unapproved AI tools in their jobs. And the truth is, most organizations have little to no visibility into how, where, or why it’s being used.

In this blog, we delve into why Shadow AI is a growing cyber threat, the risks associated with Shadow AI, and how a robust cyber GRC framework can help mitigate these risks.

Shadow AI: A Quickly Growing Cyber Risk

Consider the following examples:

• A marketing analyst uploads confidential performance reports into a public AI tool to get quick summaries and trend insights. However, this unknowingly exposes sensitive business data outside approved systems.
• A developer relies on a generative AI assistant to produce code snippets and automation scripts, accelerating delivery but introducing hidden security vulnerabilities and unclear ownership of the generated code.
• A product team uses an AI-driven analytics platform to interpret customer interactions and financial trends, making strategic decisions based on outputs that haven’t been validated for accuracy, bias, or compliance.
• A customer support manager deploys an AI chatbot on the company website without going through IT or compliance, creating potential gaps in data privacy, model governance, and response quality controls.

The examples above are just a few real-world instances of unmanaged AI adoption.

Enterprises have raised concerns about the rise of ‘vibe coding’, where developers rely on AI to generate code based on vague prompts or intended outcomes. This often leads to insecure patterns, missing validation steps, and embedded vulnerabilities. Even more concerning, these AI-generated outputs may be deployed directly into production environments without thorough code review or security checks.

Another emerging risk involves the development of internal AI agents that have overly permissive access to organizational data. These agents are typically designed to automate workflows or answer employee queries; however, without strict access controls and guardrails, they can unintentionally serve as a backdoor to sensitive systems and information.

Key Risks Resulting from Shadow AI Use

Shadow AI expands the organization’s risk surface in ways that are often invisible to security teams. Gartner has predicted that by 2030, more than 40% of global organizations will suffer security and compliance incidents due to the use of unauthorized AI tools. The key risks that enterprises are now concerned about include:

• Data Leakage: Employees may unknowingly input sensitive or proprietary data into public AI tools, leading to potential data exposure and regulatory non compliance.
• Intellectual Property Risks: Content generated or shared through unsanctioned AI platforms can compromise trade secrets or lead to IP ownership disputes.
• Model Vulnerabilities: AI models or plugins not vetted for security may contain backdoors or expose APIs to external attacks.
• Compliance and Privacy Violations: The lack of governance around data handling, consent, and storage in unapproved AI tools can result in breaches of GDPR, HIPAA, or emerging AI regulations.
• Erosion of Trust: When AI outputs are used without validation, organizations risk reputational damage due to bias, inaccuracies, or misuse of generative content.

How a Strong Cyber GRC Framework Helps Mitigate Shadow AI Risks

To counter the rise of shadow AI, organizations need a comprehensive Cyber Governance, Risk, and Compliance (GRC) strategy that blends oversight, automation, and awareness.

1. Establish Clear AI Governance Policies 

   Define what AI tools and models are approved for use, outline data-sharing boundaries, and specify accountability for AI-driven decisions.

2. Map and Monitor AI Usage Across the Enterprise 

   Use continuous monitoring and AI discovery tools to identify where and how AI is being used — both formally and informally — across departments.

3. Integrate AI Risk into Cyber and Operational Risk Assessments 

   Incorporate AI-related threats into enterprise risk frameworks to evaluate potential data, compliance, and reputational impacts.

4. Automate Controls and Compliance Monitoring 

   A unified Cyber GRC platform can automate policy enforcement, track adherence to AI governance rules, and generate real-time compliance insights.

5. Educate Employees on Responsible AI Use 

   Awareness programs can help employees understand the implications of shadow AI, ensuring innovation doesn’t come at the cost of security.

Turning Shadow AI into Strategic Advantage

Shadow AI doesn’t have to remain a hidden threat. By embedding AI oversight into the organization’s Cyber GRC framework, enterprises can empower safe, compliant, and responsible AI adoption. With proactive governance and automated controls, organizations can turn what was once a blind spot into a strategic advantage, accelerating innovation without compromising trust or security.

Build Cyber Resilience with MetricStream’s Cyber GRC

Staying ahead of today’s fast-moving threats requires more than reactive defences. It demands a connected, proactive approach to cyber risk, compliance, and controls. MetricStream’s Cyber GRC brings all of this together in one unified solution to help organizations strengthen resilience and make smarter, risk-aware decisions.

With the MetricStream Cyber GRC solution, you can:

• Accelerate IT and cyber risk assessments with up to 66% time savings and streamline workflows across teams.
• Strengthen IT and cyber compliance by aligning with ISO 27001, NIST CSF, NIST 800-53, and other leading frameworks.
• Centralize cyber risk management with structured assessments, continuous monitoring, and closed-loop issue remediation.
• Simplify IT policy management through automated creation, review cycles, and exception tracking.
• Manage third-party cyber risk using standardized assessments and real-time vendor insights.
• Quantify cyber risk in monetary terms using FAIR and simulation models to support better decisions.
• Improve visibility and reporting with real-time dashboards for leaders, regulators, and the board.

Get a personalized demo to explore Cyber GRC’s capabilities in real time.