Avoiding the Risks of Shadow AI with a Proactive Approach to IT

Thanks to quick daily strides in digital technology, artificial intelligence (AI), and machine learning, businesses have more innovation potential than ever before. 

Today, almost any business can leverage the latest breakthroughs in automation, personalization, and analytics to get ahead. Such innovations are utilized across virtually every industry, including but not limited to:

• Healthcare: Healthcare providers can intervene early and provide targeted preventive care by using predictive analytics to determine a patient’s risk of certain conditions or diseases.
• Finance & Banking: Financial institutions can automate the collection and processing of financial data—including invoices, receipts, and transactions—for more efficient bookkeeping.
• Sales & Marketing: Predictive modeling is often used to forecast future sales, optimize supply chains, and estimate the potential value of a customer over their lifetime.
• Manufacturing: Access to historical sales data, market trends, seasonality, and other analytics allows businesses to improve their inventory management, production planning, and logistics.

With such powerful tools and capabilities available to them, organizations can now precisely capture, organize, and measure all types of data, metrics, and patterns that could once only be analyzed manually. Undoubtedly, the sudden increase in advanced software applications and AI programs like ChatGPT has provided optimization and growth potential for countless areas of business. 

Recognizing the Reality

These new opportunities also come with new vulnerabilities and risks, making the responsible use of this technology absolutely crucial to maintaining safety, security, privacy, and compliance.

Essentially, today’s users are left mostly to their own devices when trying to determine the ethical, legal, and societal implications of their digital actions. Shadow IT is just the beginning of this ambiguity, and Shadow AI is likely to amplify these effects if measures are not taken to lessen the impact of unauthorized usage.

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Defining the Shadows

Despite existing software regulations, many users are unaware or simply ignorant of the ways in which their data inputs are being used and stored. AI programs are so ubiquitous nowadays that teams sometimes get ahead of formal business processes and technology procedures, which can cause serious issues in the long run. 

When internal teams aren’t aware of what’s right and wrong regarding data input, or simply aren’t motivated to comply, they often wind up lost in the shadows.

What Is Shadow AI?

Since the use of Generative AI (GenAI) tools has gone mainstream, many organizations are developing an implementation strategy for their business. However, some employees may take it upon themselves to utilize these tools without express permission or authorization from a qualified superior. 

In essence, this is what constitutes the concept of Shadow AI, or the “unauthorized utilization of artificial intelligence tools, algorithms, or models” by team members within an organization. Although leveraging advanced tools can lead to exponential boosts in creativity and productivity, many users are unaware of the organizational threats that result from the misuse of these programs.

What Is Shadow IT?

Similarly, Shadow IT is a phenomenon that occurs when employees or users bring software tools into their organization without IT’s knowledge or oversight. It may seem harmless and well-intended, but the unsupervised addition of unapproved or unvetted software applications can present numerous security and financial risks. 

How Do They Affect Each Other?

In both instances, technology is being incorporated without appropriate authorization or governance, ushering in a unique and unfamiliar danger for organizations of all kinds. Over recent years, many businesses have seen or even experienced firsthand the possible security, privacy, and legal risks of Shadow IT. 

From inefficient data analysis to the introduction of malware and ransomware, unsanctioned use of technology tools can open up a dark realm of vulnerabilities. Throwing GenAI programs into that equation only multiples this volatility, and below we explain why.

Understanding the Risks

Technological progress isn’t slowing down any time soon, but the constant creation and development of advanced software applications isn’t the only thing driving today’s tech innovations. The widespread adoption of new technologies by consumers and corporations alike is occurring at breakneck speed. As a result, users get their hands on new software products before they’re aware of the associated risks.

This ease of use and program accessibility leads to the onset of shadow frontiers. Let’s look at some of the risks today’s exciting IT applications and powerful AI programs pose for both users and organizations alike.

AI Risks

The power of AI comes with numerous creative and experimental benefits, especially for businesses. However, irresponsible or unmonitored use of these programs can result in the following drawbacks:

• Oversharing institutional or personal data: When inputting data into applications like ChatGPT or Google Bard, users need to be aware of the ways information is being used and stored. Whether the input is personal identifiable information (PII) or sensitive corporate data, many of these programs generate a living record, risking potential exposure or data leaks.
• Stolen intellectual property: Unfortunately, AI algorithms are increasingly used to enable infringement of copyrighted or proprietary assets. From unlicensed content to “deepfakes,” AI algorithms are blurring the boundaries between what is and isn’t considered “derivative work,” causing a collision between technology and copyright law.
• Lack of accountability: Many of today’s AI algorithms operate in what is essentially a black box—the majority of users don’t know or care how these programs arrive at their outputs. This perpetuates the questionable accountability behind the use of AI. Put simply, when the program generates an incorrect, misleading, or even harmful response, who exactly is to blame for the damage that results?

Shadow Warnings

The above implications are only exacerbated by the existence of Shadow AI and Shadow IT within an organization. If even authorized use of these systems can cause problems, imagine the havoc wreaked when their implementation goes unchecked. Plus, the rise of remote work increases the chances of employees utilizing technology without express approval or supervision.

One of the most substantial risks of unauthorized software is the unintentional introduction of unvetted data sets. GenAI applications, for example, operate using millions (and even billions) of parameters trained to identify relationships, make predictions, and generate a suitable response. Although the algorithm itself has no opinions or biases, output is based on human-derived data input and rules. This causes the result to be unintentionally flawed or biased, skewing decision-making with inaccurate or subjective insights.

This significant risk applies to both Shadow AI and Shadow IT. When users aren’t sure how the program they’re using operates, or on what data the outputs are based, they can’t be sure their use of the technology is ethical, safe, or even legal.

Solutions for Mitigating These Risks

Although it’s partly the user’s responsibility to take precautions to avoid the above risks, organizations should also take proactive measures to minimize these concerns. For example, businesses should implement ongoing training opportunities on the proper utilization of AI tools, including information regarding prompting techniques and data literacy.

Organizations can also reduce such risks by establishing company-wide policies that encourage the healthy, responsible use of AI tools and programs. Employees should be able to easily access standard procedures and protocols for what constitutes acceptable use. Moreover, leaders need to encourage and incentivize their subordinates to use these references as resources in their daily obligations.

Lastly, responsible data access and usage relies heavily on implementing appropriate system permission controls. Organizations must pay close attention to who has access to what information, functionalities, and programs—and why. These permissions should also be regularly audited to ensure maximum accessibility and security.

Balancing Compliance and Privacy

When users aren’t aware of or educated about proper data literacy and the latest cybersecurity protocol, their actions within an interface can put a business’s entire infrastructure at risk. At the least, a lack of data caution can lead to law or compliance regulation violations, resulting in fines or other penalties. At worst, users and entire organizations may release confidential, proprietary, or otherwise volatile information. 

As we know, any online or cloud-based program comes with its share of security and privacy risks, both personal and organizational. However, the potential for data leaks is much higher when employees use unauthorized software, especially if they’re haphazardly entering sensitive data into unencrypted GenAI applications. The key to balancing both legal compliance and peak data privacy is proper cyber awareness training and collective ongoing efforts to expand internal data literacy.

Prioritizing Data Literacy and Conscientious Connectivity

In the end, the answer we seek is not whether Shadow AI or Shadow IT is the greater risk to users. The driving point is that both shadow frontiers present a notable threat to individuals and organizations when not utilized and monitored responsibly. 

Many of us protect our personal information with diligence, but are we treating institutional data with the same level of data literacy? The prevalence of these shadow frontiers suggests not. 

To avoid constantly playing catch up, organizations must avoid relying on a reactive approach to these circumstances and instead put incentives in place to prevent unauthorized technology usage without hindering ingenuity. A proactive approach requires detailed policies and guidelines about the present and future use of software applications, and it may even involve making enterprise solutions available to keep data sufficiently protected.

That being said, the advantages of leveraging the latest cloud-based and AI technology for performing day-to-day business obligations cannot be downplayed. Despite any risks of misuse, these advancements have opened avenues for success that business leaders could only imagine several decades ago. To explore these innovations further and stay ahead of the curve, Ntiva offers the latest insights on AI integrations, cybersecurity, Microsoft 365, and more in our various On-Demand Webinars.