The Business Prompt Playbook · Article 3 of 8
15 AI Terms Explained in Plain Business Language
By Jane Chew · AI Strategy Coach, DigitalAI Business Club · May 2026
Conversations about AI are full of terms that feel technical but are not. Once you know what they actually mean — in plain business language — you can make smarter decisions about which tools to use, what to ask them, and what to watch out for. This glossary covers the 15 terms that come up most often.
Foundation terms (1–5): What AI actually is
Term 01
Artificial Intelligence (AI)
What it is: Software that learns patterns from large amounts of data, then uses those patterns to answer questions and complete tasks.
Business translation: A smart assistant that has read an enormous amount of information and uses that knowledge to help you work faster — if you give it the right instructions.
Term 02
Large Language Model (LLM)
What it is: A type of AI trained on massive amounts of text — books, websites, articles, code — and able to generate human-quality text in response to instructions. ChatGPT, Claude, and Gemini are all LLMs.
Business translation: The engine behind the AI tools you use every day. When you type a prompt, you are talking to an LLM.
Term 03
Machine Learning (ML)
What it is: The method used to train AI. The system is exposed to large datasets and adjusts itself to recognise patterns — without being explicitly programmed with rules.
Business translation: How AI learns. Like training a new hire by giving them thousands of examples until they understand the pattern on their own.
Term 04
Training Data
What it is: The text, data, and information used to teach the model. It includes books, articles, websites, research papers, and code from across the internet.
Business translation: The AI’s entire education. Everything it knows comes from this. It is why AI is knowledgeable across many domains — but also why it may not know your specific business without context from you.
Term 05
Hallucination
What it is: When the AI produces an answer that sounds confident and plausible but is factually incorrect. It is not lying — it is completing a pattern based on insufficient information.
Business translation: Always verify specific facts, names, statistics, and legal details that the AI provides — especially when context was limited in your prompt. More context = fewer hallucinations.
Prompt terms (6–10): How you communicate with AI
Term 06
Prompt
What it is: The instruction or message you give the AI. Everything you type into ChatGPT, Claude, or Gemini is a prompt.
Business translation: Your brief to the AI. The quality of your brief determines the quality of the output.
Term 07
Prompt Engineering
What it is: The skill of writing clear, structured prompts that produce high-quality, relevant AI outputs. It is not coding — it is a communication skill.
Business translation: Learning how to ask AI the right questions in the right way. This entire article series is about building this skill.
Term 08
Context Window
What it is: The maximum amount of text an AI can hold in its working memory during a single conversation. When a conversation grows beyond this limit, the AI begins to forget earlier parts of the discussion.
Business translation: If your AI seems to forget your instructions after a long conversation, it has hit its memory limit. Restate key instructions or start a fresh session.
Term 09
Token
What it is: A small unit of text — roughly three to four characters on average. AI models process your input token by token, not word by word.
Business translation: Tokens are how AI tools measure and charge for usage. Longer prompts and outputs use more tokens and may cost more on API-based platforms.
Term 10
System Instructions
What it is: A hidden layer of instructions given to the AI before any user conversation begins — defining its role, personality, constraints, or areas of focus.
Business translation: If you build a custom AI assistant for your business (e.g. a customer service bot), system instructions are where you define how it behaves. Think of it as the standing brief you give a staff member before their first day.
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Take the Free AssessmentAdvanced terms (11–15): What powers the results
Term 11
Temperature
What it is: A setting that controls how creative or predictable the AI’s responses are. Higher temperature = more creative and varied. Lower temperature = more focused and consistent.
Business translation: You cannot usually change this directly in standard chat tools — but you can influence it through your prompt. Strict, structured prompts push the AI toward lower-temperature (precise) outputs. Open-ended prompts produce more creative responses.
Term 12
RAG — Retrieval-Augmented Generation
What it is: A technique where the AI searches a specific knowledge base or set of documents before generating its answer — rather than relying only on what it was trained on.
Business translation: RAG is how you build an AI assistant that knows your business. Feed it your product catalogue, SOPs, or FAQ documents, and it answers questions using your actual information — not general internet knowledge.
Term 13
Fine-Tuning
What it is: Retraining an existing AI model on a smaller, specific dataset so it becomes highly capable in a particular domain or style.
Business translation: Think of it as specialist training on top of a general education. A fine-tuned model for a Malaysian property firm would understand local regulations, property types, and buyer language far better than a general-purpose model.
Term 14
Inference
What it is: The process of the AI generating a response — when it takes your prompt and calculates its output. Every time you send a message and the AI responds, that is inference happening.
Business translation: Inference is what you pay for in API-based AI tools. Each response = one inference event. Understanding this helps you think about AI cost structures if you plan to build AI-powered tools for your business.
Term 15
Parameters
What it is: The internal variables of the model — the millions or billions of numeric values it learned during training that determine how it responds. More parameters generally means a more capable model.
Business translation: When someone says “a 70 billion parameter model,” they mean a very capable — and computationally expensive — AI. You do not need to manage these. But knowing what they refer to helps you evaluate which AI tool is appropriate for which task.
These 15 terms are the foundation of confident AI conversations. You do not need to master them — but knowing what they mean will help you make better tool choices, ask better questions, and avoid common misunderstandings when working with AI consultants or technology partners.
In Article 4, we move into the hidden variables that change your AI results — even when you use the same prompt structure. Understanding these separates competent AI users from genuinely skilled ones.
Frequently Asked Questions
What is AI hallucination and how does it affect my business?
AI hallucination is when the AI produces an answer that sounds confident and plausible but is factually wrong. It happens when the prompt lacks enough context, so the AI fills gaps with its best pattern-match rather than verified information. For business use, always verify specific facts, figures, legal details, and statistics that the AI provides.
What is the difference between ChatGPT, Claude, Gemini, and Perplexity?
All four are large language models. ChatGPT (OpenAI) is strong at structured reasoning and creative tasks. Claude (Anthropic) is strong at writing quality and nuanced analysis. Gemini (Google) integrates with Google products and is fast at summarisation. Perplexity specialises in web-sourced, real-time answers with citations. All four respond to the same 4-part prompt formula.
What does ‘context window’ mean and why should business owners care?
The context window is how much information the AI can hold in memory during a single conversation. When the conversation grows beyond this limit, the AI begins to forget earlier parts. For business use, long briefings or documents may need to be broken up and key instructions restated periodically.
What is prompt engineering and is it the same as coding?
Prompt engineering is the skill of writing clear, structured instructions that guide AI tools to produce high-quality outputs. It is not coding — it is a communication skill, closer to writing a good brief than to programming. Any business owner can learn the fundamentals in a short time.
What is RAG and how is it relevant to my business?
RAG stands for Retrieval-Augmented Generation. It is a technique where the AI searches a specific set of documents or a knowledge base before answering a question. For businesses, RAG means you can build AI tools that answer questions using your own internal documents, policies, or product information — not just general internet knowledge.
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