Artificial Intelligence (AI) is a game-changer for small businesses, offering tools for content creation, customer service, and automation. However, as more businesses rely on AI-generated content, one important concept to understand is the “hallucination rate”—the tendency of AI models to generate false or misleading information.

My husband is an attorney and AI is a big topic of conversation in the legal world. Why? Because a study from Stanford RegLab and Institute for Human-Centered AI on LLM’s (large language model – basically the model that uses the AI to generate content) showed “hallucination rates range from 69% to 88% in response to specific legal queries for state-of-the-art language models.”

What.

So, if AI is just making things up for the legal world, what about other industries?

First, What Is AI Hallucination?

AI hallucination occurs when an AI system produces information that appears factual but is actually incorrect or fabricated. This can happen in many ways, such as inventing statistics, misquoting sources, or providing answers that sound plausible but have no basis in reality.

For example, if you ask an AI tool for historical business trends, it may generate convincing but completely inaccurate data if it doesn’t have access to verified sources. In customer service chatbots, hallucinations might lead to incorrect responses that could frustrate customers or even cause reputational damage.

Why Does AI Hallucinate?

AI systems are trained on vast amounts of data, but they do not “think” like humans. Instead, they predict words and phrases based on patterns. If there are gaps in training data or ambiguous prompts, the AI might fill in the blanks with incorrect information rather than admit uncertainty.

Some reasons AI hallucinations occur include:

• Limited or outdated training data – AI models rely on existing data and may not have access to the latest or most accurate information.
• Bias in datasets – If an AI model is trained on biased or incorrect information, it can reinforce those inaccuracies.
• Lack of real-world understanding – AI doesn’t “know” facts the way humans do; it processes language based on probability, which can lead to errors.

So, What’s the Solution?

1. Fact-check AI-generated content – Always verify important details, especially numbers, statistics, or legal information.
2. Use AI as an assistant, not a sole decision-maker – AI is a great tool, but human oversight is essential.
3. Train AI with custom data – If you use AI for internal knowledge bases, ensure it is trained on accurate, up-to-date information specific to your business.
4. Encourage customer feedback – If using AI chatbots or automated responses, have a system for customers to flag incorrect information.
5. Choose AI tools wisely – Some AI models have lower hallucination rates than others. Research and select AI solutions known for accuracy in your industry.

The Bottom Line

For me, I do use ChatGPT (I know! I know!). But if you can’t beat ’em, it’s probably a good way to figure out how to utilize ’em, amiright? My rules of engagagment are:

• Never use 100% AI generated content for anything – blog post, social post, newsletter, etc.
• Always read the entire item.
• Plug in either the intro or conclusion (at least!).
• Make language edits that are on-brand for your business.

AI is a powerful tool for small business owners, but understanding its limitations is key to using it effectively. By being aware of hallucination rates and taking steps to verify AI-generated content, businesses can leverage AI while maintaining accuracy and credibility.