AI chat for business
AI chat is the part of the workspace most businesses use daily, and the use cases are narrower and more useful than the marketing suggests. It is a drafting tool and a summarising tool, and it is very good at both.
The tasks it genuinely saves time on
- First drafts. A proposal, a scope of work, a difficult client email. Starting from a draft you edit is faster than starting from an empty page.
- Tightening. Taking something you wrote at length and cutting it to half without losing the substance.
- Summarising. A 40-page tender document reduced to the requirements, the deadline and the eligibility criteria.
- Reframing. The same explanation written for a technical buyer and for a non-technical one.
- Structuring. Turning scattered notes from a site visit into an ordered document.
Choosing a model for the task
With 30+ models available, the choice matters more than people expect. General guidance that holds up:
- Long documents — favour models with larger context handling, so you are not summarising in chunks.
- Careful reasoning — numerical work, logic, multi-step analysis. Use a stronger reasoning model and accept it is slower.
- High-volume simple tasks — a faster, cheaper model is fine for reformatting or short rewrites, and preserves your premium credits.
- Natural prose — this is genuinely subjective; try two on the same brief and keep the one that sounds like you.
Prompts that produce usable output
The difference between a useless response and a usable one is almost always the input. Four things to include:
- Role and audience. Who is writing, and who is reading.
- The actual facts. Paste in the real figures, dates and names. Vague inputs produce vague output.
- Length and format. “Four short paragraphs” beats “write about”.
- Constraints. What to avoid — jargon, promises you cannot keep, specific claims.
Then iterate. The second and third attempts are usually where it becomes usable, and asking for a specific change is faster than rewriting the prompt from scratch.
Checking the output
Treat every factual claim as unverified. Models generate plausible text, and plausible is not the same as correct — figures, dates, legal requirements and tax rates are the categories where confident errors are most common and most costly.
The practical rule: anything a client will rely on, or that carries a legal or financial consequence, gets checked against a source before it leaves your hands.
Frequently asked questions
What can I use AI chat for in my business?
First drafts of proposals, scopes and client emails; tightening long text; summarising documents like tenders and contracts; reframing the same content for different audiences; and structuring rough notes.
Which model should I use?
Larger-context models for long documents, stronger reasoning models for numerical or multi-step work, and faster cheaper models for simple high-volume tasks so you preserve premium credits.
How do I get better output?
State the role and audience, paste in the real facts and figures, specify length and format, and name what to avoid. Then iterate — the second or third attempt is usually the usable one.
Can I trust what the AI tells me?
Treat factual claims as unverified. Models produce plausible text, and figures, dates, legal requirements and tax rates are where confident errors are most common. Check anything a client will rely on.
Is my conversation data used to train models?
How data is handled depends on the underlying provider and plan. If you work with confidential client material, review the current terms before pasting sensitive information into any AI tool.