How to actually use AI

AI can be genuinely useful, but using it well is not about finding the perfect prompt or trusting every answer it gives you.

The useful skill is knowing when AI is a good fit, what information to give it, what not to share, and when an answer needs checking.

The central idea is simple: use AI as an assistant, not as an unquestionable authority.

Before thinking about how to prompt an AI, ask a more important question: is AI a good tool for this task?

Some tasks are good starting points because mistakes are easy to notice and the consequences are small. Brainstorming ideas, restructuring something you wrote, explaining a concept in another way, creating practice questions, or producing a first draft all fit here.

Other tasks deserve much more caution. Medical, legal, or financial decisions can have serious consequences. So can decisions that affect another person, such as judging whether someone should get a job, a loan, or another opportunity.

The rule is not “never use AI for anything serious.” It is that the higher the consequences of being wrong, the less you should rely on AI alone.

That general approach also matches current guidance for high-stakes areas such as healthcare, where AI is treated as something that should support rather than replace responsible human judgment.

A vague request leaves important choices unspecified, so the AI has to make assumptions about what you actually want.

Prompting is not about using magical words. It is about describing the task clearly enough that the AI has useful information to work with. Useful boundaries can include:

• what you actually want done;
• who the answer is for;
• the country or time period that matters;
• your budget;
• the length or format you want;
• what should be included or excluded;
• and what the AI should do when important information is missing.

You do not need all of these every time. Give the AI the information that actually changes the task.

Sometimes you do not want the AI to answer from whatever information it already has available. You want it to work from specific evidence.

Instead of asking “what are my university’s resit rules?”, give it the university regulations and ask: “answer using the attached regulations. Show me the section that supports your answer. If the document does not contain the answer, say so.”

The same idea works elsewhere. If the question depends on evidence, give the AI reliable evidence or point it toward the right kind of source. Current laws and government rules should come from official sources. Academic claims are stronger when you can trace them back to the original research. Calculations are better handled with a calculator or code than by asking a language model to guess the arithmetic. And high-stakes health questions deserve appropriate medical sources and, when needed, qualified professional judgment.

The general habit is: when evidence matters, make the evidence part of the task.

An AI chat can feel like a private conversation because the interface looks like one. But when you use an online AI service, the information you submit is processed by that service. Exactly what happens to it depends on the product, organization, settings, and privacy policy.

That means you should not assume every AI tool handles your information in the same way. Companies themselves may receive sensitive or confidential material through AI products, which is why privacy and confidentiality around these systems matter.

You do not need to become afraid of sharing anything. Use a simpler habit: only give the AI information it actually needs. Remove identifying details when they are irrelevant. Summarize sensitive documents instead of uploading the entire thing when that is enough. At work or school, use approved tools for confidential information. And before pasting something private, ask: does the AI actually need this part to do the task?

Not every AI answer deserves the same amount of checking. If you ask for ten birthday ideas, you can simply read the list and decide whether you like them. If you ask about the deadline for an important university application, check the date against the university website. If the answer could affect your health, finances, legal position, safety, or another person’s opportunities, the standard should be much higher.

A useful ladder: at low stakes, read it, judge it, edit it. At medium stakes, check the important claims against reliable information. At high stakes, use authoritative sources and, where appropriate, qualified human expertise, and do not make the AI your only source of judgment.

The principle is proportionality. Spend more verification effort where being wrong matters more.

Some details are especially easy to accept because they make an answer sound precise. Pay extra attention to:

• names;
• dates;
• numbers and statistics;
• quotations;
• citations;
• current events;
• laws and policies;
• claims about real people.

That does not mean these details are usually wrong. It means that when one of them matters to your decision, it is worth checking.

Sometimes improving the prompt is not the answer. Sometimes you need a different tool.

Need current information? Search for it. Need exact arithmetic? Use a calculator or code. Need a law or policy? Find the official source. Need to know where a suspicious image came from? Search for the original or use tools designed to trace images. Need professional judgment in a high-stakes situation? Ask an appropriate professional.

Modern AI systems can sometimes use these tools themselves, but the principle stays the same: do not expect one language model to replace every other source and tool.

Using AI well is not only about whether the answer helps you. Sometimes your use affects someone else. Before using or publishing AI-generated work, ask:

• Am I misleading anyone about what this is?
• Am I using someone’s information or work in a way I should not?
• Could this unfairly affect another person?
• What happens if the AI is wrong?
• Who is responsible for the final decision?

The answers depend on the situation. Using AI to privately brainstorm ideas is very different from creating fake evidence, impersonating a real person, or letting an automated system make consequential decisions about people without meaningful oversight.

AI risk depends heavily on the context in which a system is used, which is why frameworks such as NIST’s AI Risk Management Framework focus on the people affected, the purpose of the system, and the consequences when something goes wrong.