Generative AI (GenAI)

01why it matters for a business

Earlier business AI mostly scored and sorted: will this customer churn, is this transaction fraud, which product should we recommend. Generative AI produces drafts. That makes it useful wherever people spend time writing, designing, summarizing, or coding, which covers a large share of office work. It is also why adoption spread quickly: anyone who can describe what they want can use it.

The business risk is that generated content looks finished whether or not it is correct. Generated text can contain invented facts, generated images can misrepresent a product, and generated code can contain security flaws. The value comes when generation is paired with grounding in your data, review by someone qualified, and clear rules about where generated content may be used.

02what it looks like in practice

Insomnia Club built an AI smile preview on generative imaging for Supreme Dental: patients see their own likely outcome before they book, inside the practice's native apps. The generation is not the product on its own. It sits next to scheduling and patient records, so the preview leads straight to an appointment, which is where the business value shows up.

The same pattern applies to text. A manufacturer's sales team can generate first drafts of proposals from a library of approved specifications and past wins, with engineers reviewing the technical sections before anything goes out.

03common mistakes

• Publishing generated content without review by someone who knows the subject.
• Ignoring rights and disclosure. Check the provider's terms on ownership of outputs and any rules in your industry about disclosing AI-generated material.
• Treating every task as a generation task. Classification, search, and simple rules are often better fits.
• Feeding sensitive data into consumer tools with unclear data handling.

04related terms

• Large language model (LLM)A large language model (LLM) is an AI model trained on very large amounts of text to predict the next piece of text, which lets it write, summarize, translate, classify, extract information, and reason through problems in everyday language.
• Multimodal AIMultimodal AI is AI that can take in or produce more than one kind of data, such as text, images, audio, video, or documents, within the same model or system.
• AI hallucinationA hallucination is output from an AI model that is fluent and confident but false or unsupported: an invented fact, a made-up citation, a policy that does not exist, or a number that appears nowhere in the source.
• Shadow AIShadow AI is the use of AI tools by employees without the knowledge, approval, or oversight of the company's IT, security, or compliance teams, such as pasting customer data into a personal chatbot account or connecting an unvetted AI plugin to work email.

05where insomnia club fits