There is a cyber threat operating inside most Central PA businesses right now that did not come from an outside attacker. It was not introduced by a phishing email or a compromised credential. It was introduced by your employees, who are trying to do their jobs more efficiently, using tools their organization has not officially approved.
This is shadow AI, the AI equivalent of shadow IT, and it is almost certainly present in your organization whether you know about it or not.
What Shadow AI Looks Like in Practice
Shadow AI does not look like a threat. It looks like a team member being resourceful.
A project manager at a Lancaster County construction firm pastes a subcontractor bid into ChatGPT to get a quick summary before a meeting. An office administrator at a manufacturing company uses a free AI writing tool to draft a vendor communication. A bookkeeper at a financial services firm uploads a spreadsheet to an AI tool to clean up formatting before a client presentation. A nurse at a medical practice uses a consumer AI tool to draft a patient’s follow-up letter.
None of these people are doing something that feels wrong. They are using tools that are genuinely useful, that save them time, and that are freely available. The problem is not their intent. The problem is what happens to the data they enter into those tools.
Where the Data Actually Goes
Consumer AI platforms, the free and low-cost tools your employees are most likely to reach for without explicit guidance, operate under terms of service that most users have never read and that most businesses would not approve if they did.
Many of these platforms process your input data on external servers. A significant number retains that data and use it to train or improve their underlying models. The client proposal your project manager summarized, the vendor communication your administrator drafted, the spreadsheet your bookkeeper uploaded, all of it may be retained on servers your organization has no relationship with, governed by terms that provide no meaningful protection for your business’s confidential information.
For Central PA businesses in healthcare, financial services, insurance, and construction, industries where client data, patient information, financial records, and project details carry confidentiality obligations, this exposure is not hypothetical. It is a documented class of risk that regulators and malpractice insurers are increasingly aware of and increasingly likely to ask about.
According to Microsoft’s 2025 Work Trend Index, 78 percent of AI users at work are bringing their own AI tools rather than using employer-provided ones. For most organizations, this means the majority of AI activity happening inside their business is happening outside their visibility and outside their control.
Why This Is Harder to Detect Than Traditional Shadow IT
Traditional shadow IT, unauthorized software installations, personal cloud storage accounts used for work files, consumer applications used for business data, are increasingly visible through network monitoring and endpoint management tools. IT teams have developed practices for identifying and addressing it.
Shadow AI is harder. Most of these tools are web-based, accessed through a standard browser, and produce no unusual network traffic signature. An employee accessing ChatGPT through a corporate device on a corporate network looks identical in the logs to an employee accessing any other web application. Without an explicit policy and explicit monitoring, shadow AI activity is effectively invisible.
This invisibility does not reduce the risk. It concentrates it. The exposure is real. The organization’s awareness of it is near zero. And the gap between those two positions is where significant liability quietly accumulates.
The Policy Gap That Creates Shadow AI
Shadow AI exists because employees have access to capable AI tools and no clear guidance about what they are and are not permitted to do with them.
This is not primarily a technology problem. It is a policy problem. When an organization has not established which AI tools are approved for business use, what categories of data are off limits for AI processing, and what the consequences are for using unapproved tools, employees default to using whatever works. Because the tools genuinely do work, and because there is no signal telling them the usage is inappropriate, the behavior compounds.
The fix is a documented AI policy that answers the basic questions explicitly. Which tools are approved? What data is off limits? How should AI-generated output be reviewed before it is used externally? What is the process for requesting approval of a new tool?
That policy does not have to be lengthy. It must be clear, communicated, and in place before AI adoption is discussed more broadly. Without it, any conversation about official AI deployment, including Microsoft Copilot, is happening on top of an unknown foundation of existing shadow AI activity that the organization has not accounted for.
What Microsoft Copilot Solves and What It Does Not
Microsoft Copilot addresses the data exposure element of shadow AI directly. Because Copilot operates within your organization’s Microsoft 365 tenant, your data does not leave your environment. It is not processed on external servers. It is not used to train models that have nothing to do with your organization.
For employees who are currently using consumer AI tools because there is no approved alternative, Copilot provides a capable AI assistant within a security perimeter that your organization controls. That is a meaningful improvement over the shadow AI status quo.
What Copilot does not solve on its own is the policy gap. Employees still need clear guidance on what Copilot is and is not appropriate for, what categories of data should not be processed through any AI tool regardless of the security architecture, and how AI-generated outputs should be handled before they are used in client-facing or compliance-relevant contexts.
The policy and the platform work together. One without the other leaves part of the problem unsolved.
Join Us June 24th: AI and Copilot 101 Webinar
On June 24th at 11:00 AM ET, TCW-GAV is hosting a free live webinar, AI and Copilot 101: A Practical Guide for Central PA Businesses, co-presented by Steve Walter and Julie Hodges from Microsoft. Shadow AI, the policy gap, and what a properly governed AI environment looks like are all on the agenda.
Register for the June 24th AI and Copilot 101 Webinar
TCW-GAV: Helping Central PA Businesses Get AI Right From the Start
At TCW-GAV, the shadow AI conversation is one we have regularly with Lancaster County and Central PA businesses before we discuss any official AI deployment. Understanding what is already happening in your environment is the starting point for building an AI strategy that is both productive and controlled.
Our work with Central PA businesses on AI governance includes:
- Shadow AI assessment by identifying what tools your team is currently using without authorization
- AI policy development tailored to your industry and compliance requirements
- Platform evaluation and selection to replace unapproved tools with sanctioned alternatives
- Microsoft 365 security configuration review before any Copilot deployment
- User communication and training to close the policy gap with your team
The Threat Is Already Inside. The Response Starts With Awareness.
Shadow AI is a silent risk Central PA businesses. Address it proactively with a clear policy and a sanctioned platform to turn it from an uncontrolled risk into a managed capability.
Schedule a complimentary AI readiness consultation with TCW-GAV and we will help you understand what is actually happening in your environment before you build a plan around it.