As businesses use AI to analyze financial information and improve productivity, protecting sensitive data and choosing secure AI tools becomes increasingly important.
AI is becoming part of everyday business pretty quickly. Companies are using it to write emails, summarize documents, analyze information, create plans, and help teams work through problems faster. And as these tools get better, they’re also encouraging users to give them more information.
That raises an important question: how much information should businesses actually be putting into AI, especially when it comes to financial data or other sensitive business information?
In a recent episode of Stimulus Tech Talk, Stimulus Technologies founder and CEO Nathan Whittacre discussed AI and financial data, privacy, cybersecurity, and some of the risks businesses need to think about as these tools become part of their day-to-day operations.
Nathan’s first point was pretty straightforward: “I see people putting way too much information into AI.”
That doesn’t mean businesses should stop using AI. There are a lot of good reasons to use it. But just like any other business technology, there need to be some rules around what goes into it, who is using it, and which AI tools the company approves.
Not All AI Tools Protect Business Data the Same Way
One of the biggest points Nathan made is that there is a difference between a public consumer AI tool and an enterprise AI system that has more privacy, security, and administrative controls.
A business-grade AI platform may give companies more control over things like data retention, account access, auditing, privacy settings, and whether information can be used to train future AI models. But simply paying for an account doesn’t mean those protections are automatically turned on.
Someone still needs to go through the settings and make sure the tool is configured correctly. That becomes especially important for businesses with compliance requirements related to healthcare, financial information, cybersecurity insurance, customer contracts, or other data privacy regulations.
AI doesn’t get a pass just because it is new technology. If a business is responsible for protecting information in email, file storage, or other business applications, it also needs to think about protecting that same information when employees use AI.
What Information Should Businesses Keep Out of AI?
There are also certain types of information Nathan recommends keeping out of AI systems altogether. That includes things like Social Security numbers, bank account and routing numbers, credit card information, passwords, API keys, and other highly confidential information.
A good rule is to think about whether that information would normally be sent electronically without additional protection. If it wouldn’t be emailed to someone unknown, it probably shouldn’t be casually pasted into an AI chatbot either.
Nathan put it this way: “Assume that if you put it in there, even an enterprise data system, that it could be leaked somehow to a third party.”
That may sound overly cautious, but it’s a useful way to look at AI data security. No security system is perfect, and the goal is not to be afraid of AI. The goal is to understand the risk before putting important business, customer, or financial information into it.
Employees May Already Be Using AI at Work
Another part of this conversation that business owners need to pay attention to is something often called “shadow AI.” Even if a company has never officially adopted an AI platform, employees may already be using one.
They may be asking AI to summarize a customer document, analyze a spreadsheet, draft a proposal, review an agreement, or help them write an email. Most of the time, they aren’t trying to create a cybersecurity problem. They’re simply trying to get their work done faster.
The problem comes when there is no AI use policy telling employees which tools are approved, what information they can upload, and what information needs to stay out of those systems.
Trying to ban AI completely probably isn’t realistic for most businesses. A better approach is to give employees approved AI tools and clear rules for using them. If people have a safe, useful option that helps them do their jobs, they are much less likely to find their own workaround.
AI Still Needs Human Oversight
One of the examples Nathan shared during the episode was how he recently used AI to help review a contract. He used the tool to identify some areas he wanted to discuss and to help organize a draft for his attorney. Then he sent it to the attorney, who reviewed the actual agreement and provided the professional expertise.
That is a good example of where AI can be useful in business. It can help teams get started, organize information, summarize something complicated, or point them toward questions they may want to ask. But a knowledgeable human still needs to make the final decision.
That becomes even more important when dealing with contracts, financial decisions, regulatory compliance, cybersecurity, or anything where getting an answer that is “close enough” can create a real business problem.
What Should Businesses Ask an AI Vendor About Data Security?
For businesses looking at AI tools that may handle sensitive information, Nathan also shared several questions worth asking before signing up.
Companies should understand whether the provider uses prompts or documents to train its AI models, how long information is retained, and whether administrators can control who has access. They should also look at whether the platform supports things like multi-factor authentication or single sign-on and whether administrators can control third-party integrations.
It’s also worth asking what happens to information when an account is deleted and what the AI provider will do if there is a data breach.
Those may sound like technical questions, but they are really business-risk questions. If an application is going to hold company, customer, employee, or financial data, the business needs to know how that information is being protected.
The Goal Isn’t to Keep AI Out of the Business
AI is going to continue becoming part of the way businesses work, and there are plenty of opportunities to use it well. It can save time, help employees work more efficiently, and give companies new ways to make use of information they already have.
The important part is putting some guardrails around it. That means choosing secure AI tools, configuring them properly, creating an AI use policy, educating employees, and making sure existing cybersecurity and compliance requirements also apply to AI.
As Nathan said near the end of the conversation, the goal isn’t to keep AI out of the business forever. It’s to make sure companies are maintaining compliance and data security while still taking advantage of what these tools can do.
The full episode covers even more, including where AI data is actually stored, the difference between public and private AI models, ways businesses can control unapproved AI use, and how Stimulus Technologies is helping clients build AI policies that make sense for their organizations.
If your business is using AI now — or your employees are starting to experiment with it — this is a conversation worth hearing.
Listen to the full episode of Stimulus Tech Talk for the complete discussion on AI and financial data, AI data security, and how businesses can use these tools without creating unnecessary risk.
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