Artificial intelligence (AI) is computer software that can do tasks once thought to need human thinking, such as understanding language, spotting patterns, making predictions or creating text and images. Much of today's AI is built with machine learning, where systems learn from data instead of being explicitly programmed. It can be useful, but it also makes mistakes, so its answers need checking.
What AI means
There is no single everyday definition, but major bodies describe it in similar ways. The International Organization for Standardization (ISO) describes AI as a branch of computer science that creates systems and software capable of tasks once thought to be uniquely human.
The OECD, an international policy organisation, defines an AI system as a machine-based system that, for explicit or implicit objectives, infers from the input it receives how to generate outputs such as predictions, content, recommendations or decisions. It adds that AI systems differ in how autonomous and adaptive they are after deployment.
In plain terms: you give an AI system some input (a question, a photo, a spreadsheet), and it works out an output (an answer, a label, a forecast, a draft).
AI, machine learning, generative AI and large language models
These terms are often mixed up. Here is how they fit together.
- Artificial intelligence is the big umbrella.
- Machine learning is one way of building AI. The US standards body NIST defines it as the development and use of computer systems that adapt and learn from data with the goal of improving accuracy. ISO describes it as enabling systems to analyse data, recognise patterns and make decisions without explicit programming.
- Generative AI is machine learning that creates new content. ISO says generative AI machines do not just process data, they create, for example generating text, images, music and code. NIST describes generative AI as models that emulate the structure and characteristics of their input data in order to generate synthetic content.
- Large language models (LLMs) are a type of generative AI focused on text. Google's machine learning course explains that an LLM predicts a token or a sequence of tokens, where a token can be a word, part of a word or a single character. In everyday terms, it predicts what comes next in a piece of text.
A chatbot is a program you chat with. You type a question, and the system produces a reply.
Everyday examples of AI
You probably meet AI more often than you think. ISO lists uses such as real-time financial fraud detection, medical diagnostics, predictive analytics, document validation and call transcription. The official sites of the chat tools below also describe everyday uses such as:
- Answering questions and helping with writing, as ChatGPT's site describes.
- Writing, planning and brainstorming, as Gemini's site describes.
- Proofreading, rewrites and tone suggestions, as Grammarly's site describes.
What AI is good at
ISO lists benefits such as automating processes, handling repetitive tasks like document validation and call transcription, faster decisions and accelerating breakthroughs. A sensible way to use AI is as a helper for first drafts and spotting patterns, with a person making the final call.
The limits of AI
AI is a tool, not an all-knowing expert. These are the main limits to keep in mind.
It can state false things confidently
NIST calls this confabulation: the production of confidently stated but erroneous or false content. It is also called hallucination. A chatbot can give an answer that sounds confident but is wrong, including made-up facts. For anything important (health, money, legal matters, study references), check the answer against a reliable source.
It can reflect bias
NIST lists harmful bias as a risk, describing it as the amplification and exacerbation of historical, societal and systemic biases.
It can affect your privacy
NIST also lists data privacy as a risk, including leakage and unauthorised use or disclosure of data. As one example, the ChatGPT website states that chats may be reviewed and used to improve its AI models. Read the privacy settings of any tool you use, and avoid pasting in passwords, client details or other sensitive material.
It can spread misinformation
ISO lists deepfakes, misinformation, biases, copyright issues and job displacement among the real concerns. NIST also lists information integrity as a risk, describing a lowered barrier to entry to generate content.
Rules are developing
The Australian Government says it focuses on high-risk uses of AI, with testing, transparency and accountability measures, while low-risk AI can largely continue unimpeded. It has also published 8 voluntary AI ethics principles for organisations. ISO says AI still operates in a largely unregulated space, so personal care and good judgement matter.
How to start using AI tools
- Pick one task. For example, summarise an article, draft an email, brainstorm ideas or explain a concept.
- Be specific. Say who the answer is for, how long it should be and what tone you want.
- Check the result. Verify facts, names, numbers and quotes before you rely on them.
- Protect private information. Leave out anything you would not want stored or reviewed.
- Follow the rules. If you use AI for school or work, follow your school's or employer's policy and disclose AI use where required.
Here are a few tools to try, based on what each official site says:
- ChatGPT is positioned for answering questions, writing, making images, handling tasks and coding, and its site offers a way to get started for free.
- Claude is Anthropic's AI. Its pricing page lists a Free plan at $0, described as free for everyone.
- Gemini is described on its site as Google's AI assistant for writing, planning, brainstorming and more.
- Perplexity describes itself as a free AI-powered answer engine.
- Grammarly describes itself as an AI writing tool. Its site lists proofreading, rewrites and tone suggestions, and says it works in over 1 million web and desktop apps.
Free options and limits change often, so check each site before you sign up.
How we chose
Definitions come from the official websites of ISO, the OECD, NIST, Google for Developers and the Australian Government. Product descriptions were checked against each tool's official site on 20 October 2026. Where we could not confirm a detail, we left it out.
Frequently asked questions
What is AI in simple terms?
AI is software that performs tasks once thought to be uniquely human, such as understanding language, recognising patterns and making predictions. Much of it is built with machine learning, which uses data.
What is the difference between AI and machine learning?
AI is the broad field. Machine learning is a method within it where systems learn from data to improve their accuracy, instead of being given a rule for every situation.
What is generative AI?
Generative AI creates new content, such as text, images or code. Chatbots that write text are one example.
What is a large language model?
A large language model is a type of generative AI that works with text. Google's machine learning course explains that it predicts which token (word, part of a word or character) is likely to come next.
Is AI always right?
No. AI can produce confidently stated but false content, which NIST calls confabulation. Always check important facts.
Is it safe to share personal information with AI tools?
Be cautious. Some services say chats may be reviewed and used to improve their models. Keep passwords and sensitive details out of chats, and read the privacy settings.
Will AI take my job?
Nobody can say for certain. ISO lists job displacement among the real concerns about AI, and it also says AI handling repetitive tasks frees up human talent for creative problem-solving. Learning to use AI tools well is a practical way to prepare, whichever way your field goes.
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