WomenBizHub AI Learning Centre · Plain-English glossary
AI language can make a simple business task sound complicated. Here are 25 useful terms, what they mean and how they might show up in your working day.
You do not need to memorise technical language to make useful decisions about AI. This glossary is written for women running businesses who want to understand the terms they see in tools, articles and search results. Each entry includes an everyday example. Features and privacy settings differ between providers, so check the tool you actually use.
If you want to start with a guided introduction, read AI for Women Over 45 in Business. For answers to common first questions, see our AI FAQ.
AI basics
1. Artificial intelligence (AI)
Computer systems that perform tasks associated with human intelligence, such as recognising patterns, understanding language or creating content. AI is an umbrella term for many different approaches and tools.
Business example: A tool groups recurring customer questions so you can decide what to explain on your website.
2. Machine learning
A way to build AI systems by learning patterns from data rather than writing a separate rule for every situation. The quality of the data and the design of the system affect the results.
Business example: An email service learns which messages are likely to be spam.
3. Generative AI
AI that creates new material, such as text, images, audio or code, in response to instructions. The result can look convincing even when a detail is wrong, so review it before using it.
Business example: You ask for three draft subject lines for your next newsletter and choose one to rewrite in your own voice.
4. Chatbot
A tool you interact with through a conversation. Some chatbots follow fixed rules; others use generative AI to respond more flexibly. The word tells you how you interact with it, not how reliable its answers are.
Business example: You ask a chat assistant to suggest a clearer answer to a common enquiry.
5. Large language model (LLM)
A type of AI model trained on large amounts of text to work with language. It can draft, summarise and answer questions, but it does not automatically know your current prices, policies or customer needs.
Business example: A writing assistant produces a first draft of a service description that you then fact-check.
Prompts and answers
6. Prompt
The question, instruction or material you give an AI tool to guide its response. A useful prompt can name your audience, goal, format and any facts the tool must use.
Business example: “Suggest three friendly headings for a public page about my bookkeeping service for first-time business owners.” Read our guide to writing better prompts.
7. Context
The background information available to the tool for a particular task. Clear context helps it make a more relevant draft; it cannot safely fill in facts you have not provided.
Business example: State that you serve local start-ups and prefer straightforward language before asking for an About page outline.
8. Model
The trained system behind an AI feature. Different models and versions have different capabilities, limits and costs. A familiar app may offer more than one model.
Business example: You choose an available model that can work with an image when you want help describing a product photo.
9. Token
A small unit of text that a language model processes. A token may be a word, part of a word or punctuation. Tool limits and some usage charges are measured in tokens.
Business example: A very long document plus a long prompt may exceed a tool’s input limit.
10. Hallucination
An AI response that contains invented or false information presented as though it were true. It may happen even when the wording sounds confident or a source is mentioned.
Business example: A draft claims you offer weekend appointments when you do not. Check facts against your actual service details before publishing.
Tools and features
11. Multimodal AI
AI that can work with more than one kind of input or output, such as text, images and audio. Exactly what it accepts or creates depends on the tool.
Business example: You share a public flyer image and ask for a plain-text description you can edit.
12. Image generation
Using generative AI to create an image from a description or reference. Review details carefully, especially words inside the image, branding and anything that might imply a real person or event.
Business example: Create an abstract banner for an article, then check it suits your brand before uploading it.
13. Automation
Setting up steps to run when a condition is met. Automation can use ordinary software rules, AI or both. You decide which steps require human review.
Business example: A form submission creates a draft follow-up email for you to approve.
14. AI agent
An AI-based system set up to pursue a goal through multiple steps, sometimes using tools or taking actions. What it can do and what approvals it needs vary by product and setup.
Business example: An agent might gather public information for a market research draft, but you check the sources before making decisions.
15. Memory
A feature in some AI products that keeps selected information across conversations so later replies can be more relevant. What is saved, and how to inspect or remove it, depends on the provider and settings.
Business example: A tool remembers that you prefer concise newsletter drafts. Check its controls before asking it to remember business details.
Trust and privacy
16. Training data
Information used when building or improving a model. This is different from the information you enter during a particular chat, although a provider’s settings and terms may affect how that information is handled.
Business example: Before uploading client notes, check the service’s data policy and whether you can complete the task with made-up examples instead.
17. Personal data
Information about an identifiable person, such as a customer’s name linked to an order or contact details. Handle it carefully when considering what to share with third-party tools.
Business example: Replace a real customer’s details with placeholders when asking for a general reply template.
18. Data controls
The settings and account choices a service offers for information you share, such as chat history, retention or use to improve models. Their names and effects vary, so read the provider’s current guidance.
Business example: Review the settings for a new AI account before entering confidential business material.
19. Bias
A pattern of unfair or unbalanced results. Bias can come from training data, design choices or the way a task is framed, so AI outputs still need human judgement.
Business example: A draft repeatedly assumes every business owner has a full-time team. Revise it to reflect your actual audience.
20. AI literacy
Knowing enough about AI tools to use them thoughtfully: what they can help with, where they can fail, what to verify and what information to protect.
Business example: You use AI to outline a blog post, then check every factual claim and add your own experience.
Search and visibility
21. Search engine optimisation (SEO)
Improving a website so search engines can access and understand useful pages, and people can find answers to relevant searches. Clear writing, helpful content and accessible pages all matter.
Business example: A page states whom you help, what your service includes and where you work.
22. AI search
Search experiences that use AI to summarise or answer a question, sometimes drawing on web pages and showing source links. Different services choose sources differently; appearing in an answer is never guaranteed.
Business example: A potential customer asks an AI search service for a local provider. Your public service page may help it understand your offer.
23. Grounding
Providing an AI system with relevant source material, such as a document or retrieved web page, to inform its answer. It can make an answer easier to check, but a source can still be outdated or misread.
Business example: Give a tool your current public services page and ask it to use only that page when drafting a short summary.
24. Retrieval-augmented generation (RAG)
A method in which a system retrieves relevant information and gives it to a generative AI model to help form an answer. Retrieval does not make the final answer automatically correct.
Business example: A support assistant searches your current help articles before drafting a response to a customer’s question.
25. Structured data
Machine-readable information added to a web page, often using Schema.org vocabulary, that helps eligible search systems understand its content. It should match what visitors can see and does not guarantee special search placement.
Business example: A page’s Article data identifies its headline and author. Start with our guide to making your business easier for AI to find.
Keep learning
Pick one term you have seen recently and try it on a small task. Our 50 practical ways to use AI in your business offers ideas; the beginner AI FAQ answers the questions that tend to follow.
For deeper technical definitions, see the Google Cloud generative AI glossary. For how Google describes AI features in Search, see Google Search Central.
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