Apr 18, 2025
There is a growing challenge within AI-driven communication: Hallucinations.
A recent study from Vectara (2024) found that 32% of all long AI responses contain hallucinations, meaning false or fabricated information. For B2B tech companies relying on AI agents for content creation, briefings, or reporting, this is something you need to consider.
But why do hallucinations occur in the first place?
Unlike a traditional database, which retrieves accurate answers based on stored facts, large language models (LLMs) like GPT operate on probability. They predict the next word in a sequence based on patterns in their training data, not on verified truths. This means they can generate fluent and convincing text that sounds right but is not always accurate.
Here are five ways to reduce hallucinations and ensure quality in your AI outputs:
1️⃣ Ground AI with reliable sources: Use retrieval-augmented generation (RAG) to feed your AI bot with verified company data, documents, or research before content is generated. It's a game changer for accuracy.
2️⃣ Limit prompt complexity: Too vague or broad prompts increase the risk of hallucinations. Be specific in your inputs and clearly define persona, scope, and format.
3️⃣ Instruct AI to avoid unverifiable content: In your prompt, explicitly tell the AI to avoid claims it cannot verify or that lack clear sources. For example: "Include only facts that can be traced to a reliable source. If uncertain, omit the claim."
4️⃣ Add citations or require source references: Prompt your AI to cite sources or tag parts of its output with origin information. This signals both uncertainty and provides you material to fact-check.
5️⃣ Regular reviews and human oversight: Even the best models need supervision. Set up periodic reviews of AI output, especially if you are using bots in publicly directed communication.