What Is Shadow AI?

Shadow AI is the use of any unauthorized artificial intelligence product in a business setting. If a company’s security team doesn’t know about the tool and what users are deploying it for, shadow AI can create a major blind spot in cybersecurity infrastructure. Without visibility into where company data is going, teams will struggle to identify exposure risks and apply security controls.

Shadow AI vs Shadow IT

Both shadow AI and shadow IT refer to the unauthorized use of software, often when an employee downloads a platform or tool to help them out at work. Shadow IT is a much broader category, spanning across unapproved SaaS tools, file-sharing platforms, or even personal devices.

Shadow AI is a subsection of shadow IT that only applies to products, tools, and systems powered by artificial intelligence. These could include generative AI models or AI-driven analytical engines. Shadow AI tends to be more problematic than shadow IT, as many generative AI tools require users to enter images, text, or code to work, which might have sensitive data contained within.

Top Causes of Shadow AI

Shadow AI is commonly a byproduct of employees wanting to embrace digital transformation but not having the designated pathway to do so officially. If an employee hears about an AI platform that could boost their productivity, they might want to give it a go, even if your company hasn’t approved it.

The vast majority of shadow AI is not actively malicious. Its real danger lies in individuals accidentally entering private information into these tools, like sharing sensitive company data with an AI analytics platform. A small fraction of shadow AI is custom-built by malicious groups to act as malware, often distributed through targeted marketing ads to employees in related industries.

There are three main causes of shadow AI that businesses should address:

• Ineffective Tool Integration Policies: If your company doesn’t provide a clear pathway that employees can use to ask IT to review and assess new AI tools, they might avoid any official routes. A slow or complex process will dishearten employees, with many simply beginning to use these tools in secret instead of having to navigate long official channels.
• Workplace Pressure: AI tools sell a promise of higher productivity, faster workdays, and more efficient systems. If an employee is under a lot of pressure to deliver work or meet tight deadlines, they might turn to AI tools to try and lighten their workplace burden.
• Lack of Awareness: As with shadow IT, most employees don’t realize why using an unauthorized platform could create a cybersecurity problem in the first place. Your organization should focus on explaining to its employees how shadow AI could lead to data exposure.

Why Bans on AI Platforms are Ineffective

Banning AI platforms without giving people the tools to solve the underlying problems that lead them to need these services typically aggravates the situation. Especially considering how many organizations are now turning to AI in some respect, blanket bans on AI platforms may simply send a message to your employees that your company isn’t willing to adapt or innovate.

There are a few reasons why AI bans are ineffective:

• Bans Lead to Shadow IT: If something is banned, there is zero chance that an employee will approach your IT team and ask them to test a platform for them. Removing this pathway instantly means that all new AI infrastructure in your business will be shadow AI.
• Bans Could Decrease Productivity: A blanket ban on AI could mean that employees no longer have access to tools that were helping them finish their work. This may create even more pressure on the employees, leading to more shadow AI.
• AI is Fairly Unavoidable: Seemingly every SaaS product has recently begun launching an AI version within its products. Everything from Slack and Teams to CRM platforms has AI integrations, making a ban seem hypocritical.

Main Risks of Shadow AI

As an IT team doesn’t know a shadow AI tool is operating in their organization, they don’t know to apply compliance policies and ensure data is handled effectively.

The main risks of shadow AI stem from how it reduces IT admin visibility over the system:

• Data Leakage: Leading AI platforms like OpenAI actively state on their websites that user conversations are retained to help with future training. If an employee enters sensitive company details into a tool like ChatGPT, that becomes part of the training data for these AI tools.
• Regulatory Non-Compliance: If your customer data is exposed or leaked in any way, you could be in non-compliance with governance regulations. Not only does this erode customer trust in your brand, but it will also result in large fines from regulatory bodies.
• Permissions Gaps: Shadow AI tools that are implemented in your company workflows may have a high level of access by default. If that’s the case (and you have no visibility over the tool to restrict it), it creates a major opportunity for third-party exploits. If a malicious team gains access to these tools in the future, then they’ll have a security-free backdoor into your organization.
• Operational Security Gaps: The aim of a modern cybersecurity posture is to manage an extensive attack surface and ensure security policies and tools are applied correctly. When employees use shadow AI, IT teams won’t be able to audit them and ensure that they have sufficient protection at all times. Equally, if a cyber threat originates from these tools, they won’t have the necessary visibility to detect these anomalies and prevent a wider breach.

Benefits of Correct Management of Shadow AI

As the shadow AI situation often arises in response to internal frustrations, businesses can actively work on remedying the root causes that make people turn to unauthorized systems. When companies take a proactive approach and have the right procedures in place, employees are much less likely to feel the need to turn to shadow AI and shadow IT in general.

Here are some of the benefits of correctly managing the shadow AI situation:

• Enhanced Productivity: Vetting and allowing AI systems in your business means that employees can benefit from any of the productivity or efficiency optimizations these tools offer. By addressing shadow AI, your company will be more effective and innovative in the long run.
• Improved Data Security: Offering pathways where employees can verify whether an AI tool is safe to use will allow you to apply any data compliance policies to the platform. Controlling how employees use the platform will let you implement data loss prevention strategies to keep your business safe.
• Increased Systems Visibility: Properly managing the shadow AI threat will give your team complete visibility over every single tool, platform, and solution used in your business. That insight allows them to pinpoint how data moves through your organization, putting in place compliance safeguards to protect it.
• Fortified Security Posture: With the other benefits in mind, like enhanced data security and improved visibility, effectively managing the AI situation will help to dramatically improve your company’s security posture. By fully understanding the true breadth of your attack surface, your cybersecurity team can implement technology and protocols to keep all of your systems as safe as possible.

The 2025 Check Point AI Security Report shows that shadow AI is one of the leading concerns of enterprises. Correctly managing the causes of shadow AI will help keep your business safe.

Best Practices to Mitigate Shadow AI

If employees feel supported in their use of AI software and understand the potential routes they have to verify new tools, they’re less likely to use AI in secret.

Here are the best practices your business should follow to mitigate shadow AI:

• Develop Clear AI Governance Policies: When people don’t understand the rules, they might end up creating problems for your security team. Create and distribute clear AI governance policies that dictate how users can employ AI and in what situations they should avoid these tools.
• Create a Verification Pathway: Design a clear pathway that any employee can take if they want to ask security to verify a new tool. Keep it as simple as possible to reduce the likelihood of someone stopping the process halfway or skipping it altogether.
• Use AI Visibility Tools: Although shadow AI is difficult to identify, it’s not impossible to locate. Where possible, use security tools and technologies that give you a better chance of spotting unauthorized AI activity in your organization.
• Offer Alternatives: If your business doesn’t want to incorporate an AI product or finds vulnerabilities in a tool, then be sure to offer employees strong alternatives. Giving an employee an equally useful method to perform the task they wanted to use AI for will help satisfy them.

Getting rid of shadow AI is an uphill battle, but one you can begin to mitigate today by introducing new policies and committing to listening to your employees.