6 AI Governance Best Practices for Small Businesses

The rate of AI adoption in small businesses is quicker than the creation of regulations. Chatbots respond to customers 24/7. AI creates marketing content, evaluates candidates, sets prices and analyzes consumer data on numerous small platforms, and most business leaders don’t properly audit it.

That speed has led to a disparity. Few small businesses possess a legal department, compliance manager or IT personnel who review the AI applications prior to launching them. However, privacy laws, consumer protection legislation and laws on automated decision-making systems often affect small businesses in the same way they affect a big company.

These laws come in the same size, but the resources necessary to comply with them vary greatly.

Why this matters more in 2026

There is no exception for AI. If the disclosure would be misleading in the mouth of an employee, then the disclosure is also misleading when made by the AI. It is up to the company, not the company that developed the AI, to make sure the AI is truthful.

There are additional data privacy laws as well. More than 20 states currently have their own privacy laws, and some already have requirements to disclose that a customer is communicating with a bot, not with a human.

Also, there are updated rules for automated decision-making systems. California’s automated decision-making technology regulation took effect on January 1, 2026, and applies to all systems that process personal information and significantly influence decisions on matters such as lending, hiring and eligibility.

Colorado canceled the AI Act before it was ever enacted and replaced it with the new automated decision-making law in 2026. Thus, businesses using AI to make decisions on hiring, lending, pricing and eligibility need to track the latest updates, because rules from last year could become obsolete very soon.

The NIST AI Risk Management Framework has been adopted by many regulators and customers as the framework that defines responsible management of AI risk. It is voluntary, but becomes the standard practice that defines reasonable governance.

Why small businesses carry more risk, not less

The assumption that governance of AI technology belongs solely to large corporations is not uncommon. However, it affects small businesses disproportionately:

• They use AI applications in their entirety, accepting the standard configurations of the software provided by vendors without any legal or information technology analysis of its performance regarding decision-making or processing data.
• Deceptive claims related to AI or a mistake in the management of a data breach result in equal penalties for both large and small organizations.
• Customer data and AI applications are usually processed on the same integrated systems of small businesses, which fail to provide segmentation required by regulations concerning data security.
• The owner is usually the only person who examines vendor agreements; thus, there is no separate governance process.

As such, the choice of vendor plays an extremely important role in terms of governance of AI. The platform designed to perform governance tasks provides more automation compared to checklists.

Best practices

1. Implement a written information security program: This needs to include an identified individual for information security, multi-factor authentication on any system containing customer data, encryption in rest and transmission, and a tested breach response plan.
2. Consider each AI output as though it came from the company: The company should not make any guarantees that cannot be backed by the business, and there should be a way to address mistakes internally and to the customer.
3. Make sure customers know when they are interacting with AI: Increasingly, many states require disclosure. Even without this requirement, transparency protects against liability and helps build trust with the customer.
4. Control consent for automated messages: Automated text messages and phone calls fall under the requirements of the Telephone Consumer Protection Act. Consent needs to be documented and managed, including immediately honoring any opt-outs.
5. Map AI involvement in customer decisions: Identify all points at which AI impacts a decision made on behalf of the customer or applicant, and verify that the technology is capable of providing necessary disclosures and opt-out capabilities.
6. Screen AI providers the same way as you would a financial institution: Ask how the vendor manages identity authentication, data encryption, incident response and safeguards against false promises.

Marketers and business leaders can effectively implement these best practices by building an AI governance framework.

A real-life example

The practice of these concepts can be illustrated through small independent car dealers, who are an example of such entities working in a regulated sector. Independent dealers fall under the classification of financial institutions because they offer financing services, thereby putting additional requirements for data security.

According to Get My Auto, independent car dealers are most vulnerable when it comes to compliance because they lack a compliance department despite being subject to the same laws from the FTC and the states as larger groups of dealers under one roof.

These governance principles, security programs, bot disclosure, consent management and accurate claims of AI are directly related to how the chatbot, CRM and website of a dealership deal with their clients.

AI has the ability to make your small business operate faster and more efficiently as well as respond to customer needs. On the other hand, AI is able to turn small errors into public ones in no time because all claims or decisions issued by AI are considered just as valid as those issued by people who work for your company. Businesses that consider proper AI literacy and AI governance as an integral part of the implementation of AI technologies will be able to gain benefits without risks.

The rate of AI adoption in small businesses is quicker than the creation of regulations. Chatbots respond to customers 24/7. AI creates marketing content, evaluates candidates, sets prices and analyzes consumer data on numerous small platforms, and most business leaders don’t properly audit it.

That speed has led to a disparity. Few small businesses possess a legal department, compliance manager or IT personnel who review the AI applications prior to launching them. However, privacy laws, consumer protection legislation and laws on automated decision-making systems often affect small businesses in the same way they affect a big company.

These laws come in the same size, but the resources necessary to comply with them vary greatly.