You are not alone if your shadow information technology (IT) concerns grew as industrial settings digitalized. Now, you also have to worry about shadow artificial intelligence. Since these issues are relatively new to the industry, handling them both may be challenging. How can you better manage them to protect IT and OT systems?
Shadow IT describes the unsanctioned use of hardware, software or cloud services — the tools workers use without your department’s knowledge. An insecure solution can introduce security vulnerabilities into critical systems. If you don’t know it exists, it could become your company’s Achilles' heel.
Similarly, shadow AI involves the use of unauthorized AI tools, agents or platforms that bypass internal policies or oversight. It poses legal, operational, reputational, strategic and compliance risks because it may violate copyright law, expose confidential information, deliberately deceive users or output hallucinations.
The very existence of shadow AI and IT poses security risks because they expand your organization’s attack surface, inadvertently allowing hackers unauthorized access to sensitive systems or databases. Low and no-code platforms make model creation accessible to virtually anyone, facilitating the silent proliferation of shadow AI. These agents can quickly multiply across teams, rendering entire ecosystems redundant or fragile.
The convergence of IT and operational technology (OT) connects hardware and software that were traditionally kept separate. Although it is supposed to create a seamless data flow and enhance collaboration between teams, it creates a single point of failure.
Hackers are already targeting this weak spot to cripple critical systems or cause downtime. A successful breach can cause financial losses, legal consequences, reputational damage and distrust among consumers. Allowing shadow IT and AI to proliferate is akin to handing them the tools they need to succeed.
Even trusted software from reputable firms is vulnerable. In June 2025, researchers discovered how to expose sensitive data from Microsoft Copilot without user interaction. Unlike a conventional breach that hinges on phishing, the exploit bypasses human behavior entirely by manipulating how the model interacts with user data to extract confidential details quietly.
While the risks are significant, preventing workers from using unauthorized tools is easier said than done. Opaque vendor services limit visibility into extended operations, complicating detection. You may also be dealing with an acute shortage of talent proficient in AI, as the industry is still relatively new to agent implementation.
The psychology behind disobedience is complex, but data eliminates the guesswork. A 2025 survey of industrial workplaces revealed nearly 70% of line workers experience “AI resentment,” where they view automation as micromanagement rather than assistance. Many worry it devalues their autonomy and expertise.
Consequently, they deliberately work around existing systems rather than with them, leaning on shadow IT in the process. On the other hand, those who use AI daily may simply prefer the tools they’re familiar with over the company-provided alternatives.
According to Boston Consulting Group, just 36% of workers feel adequately trained to use AI. Moreover, 75% say leadership provides insufficient guidance, but 54% agree they would use agents even without authorization.
Rather than looking at shadow AI and IT as purely technical problems, you must consider the human element. Ask employees why they feel the need to use unauthorized software, knowing it puts the brand at risk. Their answers may be enlightening, helping you develop a relevant action plan.
Nearly 40% of organizations are piloting AI, while 11% have already deployed agents. With adoption on the rise, urgent action is necessary.
If you simply teach workers the dangers of shadow AI and IT, they may assume they know enough to accept the risks. Instead, you should funnel them toward an official approval process so you know what tools they may be using. You can help them feel heard while preventing security risks.
Since organizations use 110 different software-as-a-service apps on average, keeping up with updates, security patches and vendor contracts is time-consuming. Realistically, you can’t continuously monitor for possible signs of unauthorized software utilization. Automated monitoring tools help you increase real-time visibility without adding to your workload.
A reporting framework can help staff feel comfortable anonymously reporting instances of shadow AI and IT, fostering a security-first culture. However, you should consider how such a system might impact workplace relationships. To prevent tension, use it to inform decision-making rather than punish people.
A contract lifecycle management solution systematically handles all agreements from initiation through renewal or termination. By streamlining and centralizing the process, it increases visibility, enhances collaboration, reduces risks and standardizes procurement. You can use it to track and create IT vendor contracts, supporting your new approval process.
Human error is unavoidable, and no plan is foolproof. Even if you have confidence in your team, creating a safety net is a strategically sound approach. Cover remaining security gaps by moving away from traditional patching processes. Prioritize hardening your IT infrastructure and the supply chains AI depends upon.
If your facility experiences a data breach or hackers compromise critical systems, you will find out. It may take days or even months, but you will discover and respond to the incident. Shadow IT is different. Since it is challenging to detect, it may not even be on your radar. Even if you think it isn’t a problem at your business, it very well may be.
Digitalization is not slowing down — IT systems are converging with industrial OT at an unprecedented rate. You can protect your environment by rethinking internal policies, adopting life cycle management tools and hardening your infrastructure.