Shadow AI: The Hidden Risks and Rewards of Unregulated AI Use

Many employees are eager to push AI’s boundaries and discover how much they can achieve with these new tools. This enthusiasm is positive in many ways because early adopters often develop new skills and insights that help them boost productivity and streamline tasks. However, this excitement sometimes clashes with company policies, especially when it involves sharing sensitive information with large language models (LLMs) or bypassing official guidelines.

This unauthorized use of AI, often called shadow AI, is becoming more common as employees use AI tools without formal approval, creating potential security risks, regulatory breaches, and issues with managing data properly.

In this article, we’ll unpack the risks of shadow AI, discuss ways to manage them, explain why companies need to build strong governance frameworks and encourage responsible AI use in the workplace.

What is Shadow AI?

“Shadow AI” refers to the unauthorized or informal use of an organization’s AI systems that bypass IT governance protocols. This could happen without the knowledge of key departments like IT and legal, leaving the organization vulnerable. Essentially, it involves employees or vendors using AI tools outside the established governance framework, often without proper approval or oversight.

For example, when an employee uploads sensitive corporate data to a personal ChatGPT account, it introduces significant risks related to data security and compliance. Similarly, vendors might deploy AI without informing clients, leading to unauthorized AI use.

Shadow AI tends to emerge when employees lack sanctioned tools or guidance on AI usage, pushing them to explore generative AI solutions outside formal channels. For IT teams, managing unauthorized AI use can feel like walking a tightrope. They need to decide which AI tools to allow or limit, ensuring employees have the right resources while safeguarding the business. It’s about finding the right balance between allowing AI to boost productivity and maintaining strong security measures.

Recognizing this, organizations are now working on creating flexible IT policies that embrace innovation while maintaining security and control, ensuring AI tools are used responsibly and effectively.

https://youtu.be/50X0UR_GnyI?si=Un0Hy-Wpo9WV9ekN

Video source: YouTube/NextGen AI and Learning

What are The Risks of Shadow AI in Organizations?

Shadow AI presents significant risks to the security and confidentiality of company data. When employees use AI tools without official approval, sensitive information, such as legal documents, proprietary data, sensitive customer support information, and even HR records, can unknowingly be fed into these systems. Many AI platforms store or process this information, increasing the risk that it could be exposed to unauthorized parties.

This issue is heightened by the fact that these platforms may lack the security measures found in enterprise-approved tools, making sensitive data more vulnerable. Moreover, the content generated by these AI tools can bring its own set of problems. AI-generated material can be factually incorrect, violate copyright or trademark laws, or contain security vulnerabilities – especially when it involves AI-created code.

Shadow AI statistics show that a large portion of AI usage in the workplace occurs outside of corporate governance. According to a report from Cyberhaven, a data protection software company, 74% of interactions with ChatGPT, 94% with Google Gemini, and 96% with Bard take place via personal, non-corporate accounts.?

Interestingly, despite the rising use of AI, the 2024 Work Trend Index Annual Report from LinkedIn and Microsoft indicates that fewer than 40% of employees have formal training on AI usage in the workplace.

What are the Drivers and Benefits of Shadow AI Adoption?

While shadow AI poses risks, it also offers several compelling advantages when properly managed. Here’s why employees often turn to shadow AI:

Speed and Flexibility

Official tools often require lengthy approval processes, which can feel bureaucratic or slow. Employees eager to harness the power of AI to improve their work may turn to shadow AI to bypass these delays and access tools quickly. They might also gravitate toward new, unapproved tools they believe can make their workflows more efficient or creative.

Tailored Solutions

Customization is another major factor. Official AI tools can feel too generic and lack the specific functionalities employees need. As a result, teams adopt shadow AI to find more tailored solutions that better fit their unique tasks. As a rule, when employees can choose their tools, they feel more in control of their work. Being able to tailor their work environment makes employees feel more engaged and invested in the results they achieve.

Feedback for IT

When shadow AI pops up in an organization, it’s often a sign that the tools and systems officially provided by IT just aren’t cutting it for employees. This feedback can be valuable. It lets the IT team know where things are falling short, helping them figure out what changes or improvements need to be made to support better how people work.

Competitive Edge

Additionally, companies that allow for AI experimentation through shadow AI often gain a competitive edge, as they can quickly adopt and leverage cutting-edge technology before competitors. This faster adoption cycle enables teams to innovate and stay ahead in rapidly evolving industries.

While shadow AI has these appealing benefits, companies must also recognize the risks, such as data security concerns and compliance issues. However, from an employee’s perspective, shadow AI often fills gaps in current IT offerings, making their work easier and more effective.

How to Prevent and Manage Shadow AI

Identifying the presence of shadow AI in a company can be difficult because much of it happens under the radar. The challenge of monitoring unauthorized AI usage, combined with the limitations in auditing AI activity, makes detection complex.

However, there are ways to tackle this issue:

1. Create Clear AI Access Policies

One of the best ways to prevent shadow AI is to develop clear policies for accessing generative AI tools. As many employees already use these tools, it’s important to provide guidelines that balance leveraging AI’s potential with mitigating risks such as security vulnerabilities or data leaks.?

The policy should address how to manage access, which might include measures like written guidelines, configuring firewalls, and using Virtual Private Networks (VPN) to control access.

2. Communicate AI Policies Effectively

After establishing AI policies, ensure they are clearly communicated to all employees. Specify which tools can be used, their appropriate applications, and what data types are acceptable. Keeping employees in the loop with regular updates is crucial. Yet, many organizations fall short in this area.?

A study by Asana highlights this gap, revealing a noticeable disconnect between executives and individual contributors regarding awareness of AI policies. While leadership may feel they’ve communicated enough, frontline employees often remain uninformed.?

3. Provide Hands-On Training

Educating employees about AI policies doesn’t ensure they will automatically know how to use AI tools properly. Hands-on training is necessary to help employees use AI tools with high efficiency, all while reducing shadow AI risks. This can be done through webinars, hands-on workshops, or self-paced modules, and more importantly, the resources must be easily accessible and convenient for all employees.

In short, companies can reduce the risks of shadow AI by equipping employees with approved AI tools that easily fit into their everyday tasks. Failing to offer these tools, along with proper AI usage guidelines, increases the likelihood of shadow AI becoming widespread in the organization.

Shadow AI: Key Takeaways

In wrapping up the discussion on shadow AI, it’s clear that while this unsanctioned use of AI tools has its advantages, it also carries significant risks that companies cannot afford to ignore. The key is to find a balance.?

Companies need to recognize the appeal of shadow AI for employees – its speed, flexibility, and ability to fill gaps in official tools – and offer approved alternatives that meet these needs while maintaining security and compliance. By doing so, businesses can stay innovative while keeping their data and processes secure, offering employees the necessary tools without leaving gaps that shadow AI might otherwise fill.

Finally, addressing shadow AI head-on empowers the company and its employees to use AI effectively, safely, and responsibly.

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