A business law perspective from Matthew Fornaro, P.A.

At many growing companies, the first real breakdown in risk management does not come from the product, the market, or even the competition. It comes from authority. A salesperson trims a quote to close a deal faster. An operations manager promises a delivery date that no one in production approved. A project lead tells an unhappy customer, “Don’t worry, we’ll make it right,” without understanding what that promise may cost the business later. None of those people are trying to create a legal problem. Most believe they are helping. But each one may have just made a commitment the company never intended to make.

That is the problem Matthew Fornaro sees repeatedly in his practice. After more than 20 years advising entrepreneurs, startups, and established companies, he has found that many businesses do not get into trouble because they are failing. They get into trouble because they are growing, delegating, and moving quickly, while no one has clearly defined who is actually allowed to say yes on behalf of the company. As a South Florida business law attorney, Matthew Fornaro approaches that issue as a business problem as much as a legal one.

At Matthew Fornaro, P.A., that recurring issue can be understood as the permission problem. It is one of the most expensive blind spots in a growing company because it often stays hidden until the business is already in a dispute with a customer, a vendor, a contractor, or an employee.

From an Internal AI Problem to a Customer-Facing One

Early discussions about business AI risk focused mainly on internal behavior. Employees were copying confidential information into public chatbots. Teams were using unapproved tools without oversight. Companies were discovering shadow systems only after someone realized sensitive data had already moved outside the business. Those concerns remain real, and Matthew Fornaro has addressed them directly in his work on shadow AI and agentic AI.

But customer-facing AI creates a different category of risk. Once AI is answering website chats, drafting proposals, writing ad copy, or responding to customer complaints, its output is no longer just an internal efficiency tool. It starts functioning like a statement from the business itself. At that point, the legal question changes. The issue is no longer whether an employee misused a tool. The issue becomes whether the company made a representation to a customer and whether the company now has to stand behind it.

That shift is happening in quiet, everyday ways. A chatbot answers a refund question at midnight. An AI-generated follow-up email overstates a product feature. A proposal tool inserts turnaround times or pricing assumptions that no one intended to approve. None of those interactions look dramatic in the moment. But they can become expensive quickly once a customer relies on them.

Where the Exposure Actually Shows Up

Matthew Fornaro sees this risk as especially significant for growth companies because the same automation that saves labor can multiply the same error across hundreds or thousands of interactions. That exposure shows up in several predictable places.

First, AI-generated quotes and proposals can create problems when pricing is calculated incorrectly, turnaround times are overstated, or terms are inserted that no one with actual authority ever approved. Second, chatbots answering questions about product features, delivery dates, warranties, or refund eligibility may say something that conflicts with the company’s real policies. Third, AI-generated advertising copy can drift into guarantees, performance claims, or comparative language that would never survive careful review.

The same issue appears in customer service. AI-assisted support language is designed to sound helpful and confident. That is part of what makes it attractive. But when a system tells a frustrated customer that the company will “make it right,” “honor the request,” or “fix the issue immediately,” it may be creating expectations or commitments the business never intended to make.

These are not edge cases involving some rogue machine. They are ordinary examples of automation doing what it was designed to do without enough legal and operational control around what it is saying.

Why This Becomes a Legal Problem

Once AI starts speaking to customers, several familiar legal doctrines can come into play. Misrepresentation is one of them. If a customer relies on a false or misleading AI-generated statement about price, timing, performance, or terms and suffers harm as a result, the business may face a claim regardless of whether a human or a machine generated the statement.

Consumer protection and deceptive advertising concerns are another. Regulators and courts generally do not care whether the problematic language came from a human copywriter or a model. If the statement is misleading, the exposure is still there. The same is true when AI-generated sales language conflicts with the business’s actual written agreements. In that situation, the issue may move from marketing risk to contract risk very quickly. That is one reason Matthew Fornaro believes growing companies should involve a business contract lawyer before AI-generated sales and support language becomes deeply integrated into customer communications.

There is also a broader authority issue. A business may be held responsible for the statements made through a tool it chose to deploy. If the company places the chatbot on its website, uses AI in its proposals, or automates parts of the customer journey, it is difficult to argue later that the output somehow does not belong to the company. From Matthew Fornaro’s perspective, that is where the permission problem and AI risk intersect. The technology may be new, but the underlying issue is familiar: who was allowed to commit the business, and what happens when the company cannot answer that question clearly?

Why Growth Companies Are Especially Exposed

This problem is particularly acute for successful companies because growth reveals weaknesses that a smaller business can often absorb. When a company is small, the founder can spot and correct a bad promise quickly. A phone call may solve the issue. Once the company scales, more people are involved, more customers are affected, and more revenue rides on each interaction. The same informal habits that once felt efficient become expensive.

That is why Matthew Fornaro views AI governance as part of the broader legal infrastructure of a growing business. It is not enough to say that AI is being used to save time. The business has to understand whether its customer-facing automation is aligned with its contracts, its actual policies, its marketing standards, and its risk tolerance. If not, the efficiency gains may be outweighed by the cost of defending claims later. In many cases, those claims eventually land on the desk of a business litigation attorney after the problem has already escalated.

What Smart Companies Should Do Now

Matthew Fornaro does not see this as an argument against AI. He sees it as an argument for discipline. Businesses do not need to stop using AI in sales, marketing, and customer support. They do need to treat customer-facing AI with the same seriousness they would apply to any employee empowered to speak on behalf of the company.

That starts with auditing what the AI is actually telling customers. Companies should review chatbot transcripts, AI-generated proposals, marketing copy, and automated follow-up language regularly, not just at launch.

They should make sure AI outputs line up with their actual written agreements, policies, and refund rules. High-stakes statements about pricing, guarantees, delivery dates, or remedies should have a human checkpoint before they go out unsupervised.

Businesses should also establish clear approval rules for marketing and sales automation and document exactly where AI is customer-facing and where it is not.

And they should not overlook intellectual property issues created by AI-generated marketing assets, branding language, or work product, especially where ownership, originality, or use rights may later become disputed. In those situations, input from counsel experienced in intellectual property can become just as important as review of the sales language itself.

The Bottom Line

The question is no longer whether growing companies should use AI in customer communications. Most already do. The better question is whether they understand that once AI starts speaking to customers, the business may have to stand behind what it says. Matthew Fornaro’s view is that customer-facing AI should be treated the same way any other public representation of the company would be treated: reviewed, documented, and aligned with the company’s actual obligations.

For companies that are scaling quickly, that kind of clarity is not overkill. It is part of responsible growth. The businesses that handle this well will not necessarily be the ones using the least AI. They will be the ones using it with clear boundaries, real oversight, and an understanding that speed is only an advantage if it is not quietly creating legal exposure in the background.

About Matthew Fornaro, P.A.

Matthew Fornaro, P.A. is a Coral Springs-based business law firm serving entrepreneurs, startups, executives, investors, and established companies throughout South Florida and beyond. The firm focuses on business formation, contract drafting and review, business transactions, business litigation, intellectual property, arbitration, mediation, and other strategic business-law matters. Matthew Fornaro is admitted in Florida, New York, and the District of Columbia and brings more than 20 years of experience advising business owners on the legal infrastructure that supports growth.

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