Risks, Benefits, and Costs of Shadow AI

With the rapid advancement in artificial intelligence and the increasing adoption rates of AI services and tools, shadow AI has emerged as a significant concern. Like shadow IT, shadow AI involves procuring and using AI tools and technologies without the explicit approval of centralized IT or AI governance teams. This phenomenon grows as AI tools become more accessible, especially in SaaS, and employees seek innovative solutions to enhance their work efficiency.

In this article, you’ll learn more about shadow AI, its associated risks, costs, and benefits, and how to successfully identify and manage AI tools that are off the radar.

What is Shadow AI?

Shadow AI refers to the use of AI applications and models by employees or departments without the formal oversight or approval of the organization’s AI governance or IT departments. This includes AI-driven software, machine learning models, and other AI functionalities, often sourced from SaaS applications.

Employees increasingly turn to readily available AI tools to solve complex problems quickly, bypassing the traditional approval processes. While this can boost productivity and innovation, it also introduces significant risks and challenges, such as security vulnerabilities and compliance issues. Furthermore, approved SaaS applications are increasingly introducing AI-based features ranging from automated data analysis and predictive analytics to personalized user experiences. These features are introduced without consent or an opt-out option, meaning that sensitive, regulated data could be used in ways that users do not fully consent to and violate compliance requirements.

Shadow AI Examples

Common examples of shadow AI include the unauthorized use of AI tools for data analysis, machine learning platforms for predictive modeling, and AI-driven automation tools. Employees often use self-procured SaaS applications to improve productivity or create solutions with tools they cannot wait to purchase through the official IT process. These tools can range from simple AI-enhanced spreadsheet functions to complex predictive analytics and machine learning models.

Why Do Employees Use Shadow AI?

The adoption of shadow AI is often driven by the need for rapid problem-solving and the ability to leverage cutting-edge AI capabilities without waiting for corporate approval. Employees might feel that official channels are too slow or lack the specific AI functionalities they need to be effective in their roles. Furthermore, the proliferation of easy-to-access AI tools and SaaS applications empowers even non-technical users to implement sophisticated solutions.

Latest Shadow AI Statistic

Investigations into the use and impact of shadow AI reveal its growing presence in enterprises. The Conference Board reports that over 50% of employees use AI to accomplish work-related tasks. Studies indicate that a substantial portion of AI tool adoption occurs outside the formal IT and AI governance structures. Many organizations are unaware of the extent of shadow AI within their operations, which poses unrecognized risks.

Over half of employees use AI for work-related tasks.

What Are the Risks of Shadow AI?

The unauthorized use of AI tools can lead to several risks:

· Security Vulnerabilities: Shadow AI can introduce new points of entry for data breaches, as unauthorized tools may not comply with organizational security policies.

· Compliance Issues: Using unsanctioned AI tools can lead to violations of regulatory requirements, especially concerning data privacy.

· Inefficiencies in Data Management: Disparate AI tools can create silos of data and analytics, leading to inconsistent results and decision-making challenges.

· Integration Problems: Unauthorized AI applications may not integrate well with existing systems, leading to operational inefficiencies and additional costs.

· Lack of Oversight: Without proper governance, it’s difficult to ensure that AI tools are used responsibly and ethically, raising concerns about biased outputs and unethical AI behaviors.

RELATED: AI Apps: A Whole New Game of Cybersecurity Whac-a-Mole

Shadow AI Benefits

Despite the risks, shadow AI can offer significant benefits:

· Enhanced Productivity: Employees can solve problems faster and more effectively with direct access to AI tools.

· Increased Innovation: Employees can develop innovative solutions that might not emerge through official channels by experimenting with AI tools.

· Employee Empowerment: Allowing employees to explore AI tools can increase job satisfaction and retention.

RELATED: From Shadow IT to Business-Led IT: A Strategic Paradigm Shift

Shadow AI Costs

The financial implications of shadow AI can be substantial:

· Security Incidents: Breaches involving AI tools can be costly in terms of both direct financial impact and damage to reputation.

· Regulatory Penalties: Non-compliance with data protection laws due to unauthorized AI use can result in significant fines.

· Operational Disruptions: Lack of integration and standardization can cause inefficiencies and increased operational costs.

Manage Shadow AI with Grip SaaS Security Control Plane

As organizations increasingly grapple with the complexities introduced by shadow AI, the need for robust and scalable solutions to manage and mitigate the risks associated with unauthorized AI tools becomes more pressing. With its comprehensive capabilities to discover, assess, and mitigate the risks related to shadow AI, the Grip SaaS Security Control Plane (SSCP)platform provides organizations with the tools necessary to govern AI use in their IT environment.

The Grip SSCP platform enables enterprises to identify unauthorized AI tools in new and existing SaaS applications. The visibility helps IT and security teams detect AI functionality that may otherwise go unnoticed. Moreover, the platform allows organizations to evaluate potential compliance risks by asking users to confirm their intent and documenting their responses. By automating the governance processes, the Grip SSCP platform reduces the administrative burden on IT teams and facilitates a more proactive approach to security and compliance for AI applications.

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To learn more about Grip SSCP or how to effectively identify, evaluate, and mitigate the risks resulting from shadow AI, book time with our team.