2024 is the year of artificial intelligence (AI) at work. In 2023, we saw an explosion of generative AI tools, and the global workforce entered a period of AI experimentation. Microsoft’s Work Trend Index Annual Report asserts that “use of generative AI has nearly doubled in the last six months, with 75% of global knowledge workers using it. And employees, struggling under the pace and volume of work, are bringing their own AI to work.”

This phenomenon of “bring your own artificial intelligence” to work is known as “shadow AI,” and it presents new risks and challenges for IT teams and organizations to address. In this blog, we’ll explain what you need to know, including: 

• What is shadow AI?
• What are the risks of shadow AI?
• And how can companies mitigate the risks of shadow AI?

What Is Shadow AI?

You may be familiar with the term “shadow IT”: it refers to when employees use software, hardware, or other systems that aren’t managed internally by their organization. Similarly, shadow AI refers to the use of AI technologies by employees without the knowledge or approval of their company’s IT department. 

This phenomenon has surged as generative AI tools, such as ChatGPT, Grammarly, Copilot, Claude AI, and other large language models (LLMs), have become more accessible to a global workforce. According to Microsoft’s Work Trend Index Annual Report, “78% of AI users are bringing their own AI tools to work—it’s even more common at small and medium-sized companies (80%).” Unfortunately, this means employees are bypassing organizational policies and compromising the security posture that their IT departments work hard to maintain. 

This rogue, unsecured use of unsanctioned gen AI tools leaves your company vulnerable to both security and compliance mishaps. Let’s dive into the key risks that shadow AI can present.

What Are the Risks of Shadow AI?

Shadow AI risk #1: Security vulnerabilities

One of the most pressing concerns with shadow AI is the security risk it poses. Unauthorized use of AI tools can lead to data breaches, exposing sensitive information such as customer data, employee data, and company data to potential cyberattacks. AI systems used without proper vetting from security teams might lack robust cybersecurity measures, making them prime targets for bad actors. A Forrester Predictions report highlights that shadow AI practices will exacerbate regulatory, privacy, and security issues as organizations struggle to keep up​​.

Shadow AI risk #2: Compliance issues

Shadow AI can also lead to significant compliance problems. Organizations are often subject to strict regulations regarding data protection and privacy. When employees use AI applications that haven’t been approved or monitored, it becomes difficult to ensure compliance with these regulations. This is particularly concerning as regulators increase their scrutiny of AI solutions and their handling of sensitive data​​.

Shadow AI risk #3: Data integrity

The uncontrolled use of AI tools can compromise data integrity. When multiple, uncoordinated AI systems are used within an organization, it can lead to inconsistent data handling practices. This not only affects data accuracy and integrity but also complicates a company’s data governance framework. Additionally, if employees input sensitive or confidential information into an unsanctioned AI tool, that could further compromise your company’s data hygiene. That’s why it’s essential to carefully manage AI models and their outputs, as well as provide guidance to employees about what types of data is safe to use with AI. 

Now let’s break down the strategies and initiatives that you can put in place today to effectively mitigate the risks of shadow AI.

How Can Companies Mitigate the Risks of Shadow AI? 

Forrester’s 2024 AI Predictions Report anticipates that “shadow AI will spread as organizations struggle to keep up with employee demand, introducing rampant regulatory, privacy, and security issues.” It’s important for companies to act now to combat this spread and mitigate the risks of shadow AI. Here are a few strategies IT departments and company leadership, particularly your CIO and CISO, should put in place to get ahead of these issues before shadow AI invisibly infiltrates their entire organization. 

Shadow AI mitigation strategy #1: Establish clear acceptable use policies

The first step to mitigate the risks associated with shadow AI is to develop and enforce clear usage policies for employees. These AI policies should define acceptable and unacceptable uses of gen AI in your business operations, including which AI tools are approved for use and what the process is for getting new AI solutions vetted.

Shadow AI mitigation strategy #2: Educate employees on the risks of shadow AI

Next, make AI education a top priority, specifically outlining the risks of shadow AI. After all, if employees don’t know the impact of using unvetted tools, then what will prevent them from using them? Training programs should emphasize the security, compliance, and data integrity issues that can arise from using unauthorized AI tools. By educating your employees, you can reduce the likelihood of them resorting to shadow IT practices​​.

Shadow AI mitigation strategy #3: Create an open and transparent AI culture

Another key foundational step to mitigate the risks of shadow AI is to create a transparent AI culture. Encouraging open communication between employees and your organization’s IT department can help ensure that security teams are in the know about what tools employees are using. According to Microsoft, 52% of people who use AI at work are reluctant to admit to using it for their most important tasks. If you create a culture of openness, especially around AI use, IT leaders can better manage and support AI tools that reinforce their security and compliance frameworks. 

Shadow AI mitigation strategy #4: Prioritize AI standardization

Finally, in order to mitigate shadow AI, your company should create an enterprise AI strategy that prioritizes tool standardization to ensure that all employees are using the same tools under the same guidelines. This involves vetting and investing in secure technology for every team, reinforcing a culture of AI openness, and encouraging appropriate and responsible use of gen AI tools. 

Shining a Light on Shadow AI

With shadow AI unknowingly growing at companies across the globe, IT and security teams must act now to mitigate the security, data, and compliance risks that unvetted technologies create. Defining clear acceptable use policies, educating employees, fostering a culture of transparent AI usage, and prioritizing AI standardization are key starting points to shine a light on the problem of shadow AI. 

No matter where you are in your AI adoption journey, understanding the risks of shadow AI and executing on the initiatives above will help. If you’re ready to tackle standardization and invest in an AI communication assistant that all teams across your enterprise can use, Grammarly Business is here to help.