How do you allow employees to use AI productively without creating security, compliance, operational, and cost problems in the process?
That’s the question many companies are wrestling with today. While leadership teams debate AI strategy, employees have already moved ahead. They’re using ChatGPT, Claude, Gemini, and dozens of other tools every day to work faster and more efficiently.
They upload documents, paste client information, and build habits around whatever tool helps them move faster. That bottom-up adoption has merit -employees often find ways to use AI that no one in leadership would have identified. But it also exposes a business to risk.
Sensitive information may be compromised. Different teams develop different standards. Management loses visibility into who is using AI, how often, and for what kind of work, while costs grow without oversight.
Before a company pursues an advanced AI strategy, it needs a foundation: a way for employees to use AI with consistency and control.
Security: Keeping Data Safe
The most immediate risk of ungoverned AI use is security. Many AI companies train their models based on user input, unless the user opts out. Employees can accidentally — or intentionally — paste in confidential company data such as code, financials, or customer records. Uploading company data to consumer AI tools moves it to an environment a business cannot control. It exposes proprietary information in ways that are not transparent and invites data breaches. These breaches may not necessarily materialize through a malicious attack, but through routine, well-intentioned employee behavior. Once shared, that data is effectively out of the company’s hands with no way to claw it back.
For businesses in regulated industries, ungoverned use of AI in the workplace exposes more than security vulnerability; it’s a potential compliance breach, with real liability under data protection laws and industry standards like GDPR, HIPAA, or SOC 2.
Visibility: Clear Protections
Beyond security, ungoverned AI use creates a visibility problem with liability risks most companies aren’t prepared for. Without clear protections, management has no way to track which platforms employees are using, how often, or for what purpose. AI-generated work may be released without review, and no one knows until something goes wrong.
The risks are no longer theoretical.
In 2023, lawyers representing a client in federal court submitted legal research generated by ChatGPT that contained entirely fictitious court cases. The attorneys were sanctioned, and the incident became one of the first widely publicized examples of AI-generated content creating real professional liability.
The risks are different than those businesses have faced in the past. Back in the day, when employees adopted software without IT oversight, the core problem was procurement and security: businesses were using tools they hadn’t approved or controlled.
OpenAI follows the same ungoverned adoption pattern, but the liability profile is different. Shadow IT would store and transmit data, AI generates it. It produces content, analysis, and decisions that are released under your company’s name. The exposure isn’t just about what employees are accessing; it’s what AI tools are creating and releasing on your behalf.
Cost: per person or per company
Per-seat licensing models present their own challenge. At a fixed cost per user, the cost is uniform regardless of actual usage. There is no mechanism to identify where AI is being used and delivering value. There is no way to know where to concentrate investment or measure ROI.
The risk increases when different departments within a firm independently subscribe to multiple overlapping AI products, bringing up the overall IT budget. Aside from mounting costs, when different teams standardize on different platforms, it creates inconsistency in how the company communicates and operates.
Creating One Integrated Platform
The instinctive response to AI sprawl is consolidation; select a platform and deploy it across the whole organization. For some organizations, that works. But like anything else, when it comes to AI, one size certainly does not fit all. Across teams and employees, model preference can differ. While Claude may be strongly suited for a development team, the marketing team may find its writing skills lacking and opt for another tool.
At Roth & Co, we encountered the same challenge. Different teams preferred different AI models, but leadership needed security controls, visibility, and cost management.
The lesson we learned was simple: the goal wasn’t choosing a single AI model. The goal was creating a governance layer around AI usage.
We built a platform on a custom backend which governs access controls and usage monitoring, while the frontend gives employees access to several AI models through a single portal that gives employees one consistent entry point to multiple AI models, while allowing the company to monitor and manage usage centrally.
The backend dashboard allows management to see who is using AI, which tools they use, and how often. Built-in safeguards help ensure that sensitive data is handled properly and that usage stays within company policy.
To keep costs low, instead of paying for a fixed license per employee, we only pay for usage across the company, with a per user breakdown. This way, heavy users have access and occasional users don’t drive up unnecessary costs that a full license would require. Access is set by role, so employees only use the tools authorized for their role that is appropriate for the work they do.
The Real Difference
AI is quickly becoming as fundamental to business operations as email, spreadsheets, and cloud software. The question is no longer whether employees will use AI—they already are.
The real question is whether organizations will create the governance, visibility, and security needed to ensure AI becomes a competitive advantage rather than an unmanaged risk.
The companies that solve that challenge first will likely gain a significant operational edge over the next decade.
This material has been prepared for informational purposes only, and is not intended to provide or be relied upon for legal or tax advice. If you have any specific legal or tax questions regarding this content or related issues, please consult with your professional legal or tax advisor.
