How to improve AI literacy in your small business

Most small business owners we speak to have tried AI at least once.

They've drafted a social post, summarised a document or asked for help rewriting an awkward email. The results were decent, sometimes impressive. But then the doubt crept in.

Can I trust this? Am I using it properly? What shouldn't I be putting into it?

AI literacy helps you answer those questions. There's no coding to learn, or technical jargon to master (well, not really).

You simply gain the working knowledge you need to get useful output, spot problems quickly and avoid the obvious risks.

If you run a small business, that literacy now matters in the same way financial literacy does.

You don't need to be an accountant. But you do need to understand enough to make good decisions, ask better questions and know when something looks wrong.

This blog sets out the minimum you need to know to use AI confidently in your business. Practical skills, clear guardrails and a simple way to build those habits into your day-to-day work.

What "AI literacy" means in a small business

AI literacy is being able to use AI in a way that holds up in the real world.

You can get decent output, you know what it's good for, you know what can go wrong and you have a simple habit for checking the work before it leaves the building.

• You can write a prompt that gets you something useful on the first or second try, not the 10^th.

• You don't copy and paste sensitive customer details into a public tool because you've already decided what counts as sensitive.

• You can spot when an answer sounds confident but is actually vague or stitched together.

• You know when to stop and get a human answer because the risk is too high.

It also means you can teach the basics to someone else in your team without making it a big training project.

If AI only "works" when one person is at the keyboard, that isn't really a capability – it's a party trick.

A lot of AI advice online skips straight to use cases. Use it for marketing, use it for admin, use it for finance.

That's fine, but it leaves out the part that makes those use cases safe and repeatable. AI literacy is that missing layer.

But you don't learn it once and move on. You build a few habits and keep using them, because the tools change fast and the basics are what stay useful.

How AI-literate is your business today?

Do you have the basics covered or are you mostly winging it? Think about your business as it is right now and answer these questions honestly:

• Do you have a short list of jobs where AI is allowed to help, and a short list where it isn't?

• If someone new joined tomorrow, could they get a useful result from AI using one of your prompts, without bothering you?

• When you use AI for anything customer-facing, do you have a habit for checking the parts that could cause problems?

• Do you know what information you should never paste into a public AI tool, and does your team know too?

• If AI suggests something questionable, do you have a default response that slows things down, like asking for sources or assumptions, rather than taking it at face value?

If you answered "no" to a few of those, don't worry. All it means is that you haven't put the guardrails in yet.

Most businesses haven't. The upside is that you can fix a lot of this with a handful of habits and a bit of repetition.

A beginner-friendly two-week AI literacy sprint (15 minutes a day)

This is designed for real working weeks rather than a gruelling workshop. The key is to repeat it enough so the basics stick.

Week 1: Set your foundations

Start by picking two low-risk tasks where having a draft is genuinely helpful.

Good candidates are things like:

• turning messy meeting notes into actions

• rewriting a blunt email into something calmer

• summarising customer feedback to pull out themes

• drafting a first pass of a policy you'll review carefully later

On day one, write down your "safe list" and your "not worth the risk" list. Keep them short. If you already know there are areas you'd regret getting wrong, put them aside.

Over the next couple of days, create two reusable prompts. Prompts get better the more you use them. Save them somewhere your team can find, even if it's just a shared document.

Then build your checking habit. Pick one output you generated that week and do a deliberate review to make sure the information is accurate. Check names, numbers, dates, claims. Look for confident nonsense.

If you're using AI to summarise, compare the summary against the source and see what it missed or overemphasised. That's how you learn what the tool tends to do in your context.

Finish week one by setting your "data boundary". Write a simple, practical list of what your business won't paste into public AI tools.

And be specific – "customer names and contact details" is clearer than "personal data", and "bank details and invoice PDFs" is clearer than "financial information". Share it with the team and treat it as business as usual, not a scary compliance exercise.

Week 2: Apply it to one real workflow

Now choose one workflow (process) where you can save time without creating risk. If you try to do five at once, you won't learn what's working.

Pick a workflow that already exists and is easily repeatable. For example:

• turning enquiry emails into a structured reply and a follow-up task list

• cleaning up product descriptions pulled from a supplier spreadsheet

• summarising project updates into a client-friendly weekly email

• turning call notes into a short CRM update with next steps

• creating a first draft of an invoice-chasing sequence that still sounds like you

For each attempt, keep the boundaries tight. Decide what you'll feed in, what you want out and what you'll check before using it.

If it helps, write the output format into the prompt so you don't spend time reshaping the result every time.

By the end of the week, write a one-page "how we use AI here" note. Include:

• what AI is allowed to help with

• what's off-limits

• what data never goes into prompts

• the one checking step everyone must do before using AI output outside the business

• where your saved prompts live

That's enough to stop AI being a personal experiment and to let it become a shared capability.

Want a guided route instead of figuring it out as you go?

Some people are happy testing and tweaking until it clicks. Others would rather follow a short course, pick up the basics in order, then get on with work.

If that's you, Sage has created a free learning hub called AI Academy. The part that maps best to what we've covered here is its AI Literacy Fundamentals course.

It focuses on day-to-day understanding of AI, practical prompting and how to use AI responsibly at work. It also includes a short quiz so you can check what's stuck and what you've missed.

If you'd like a structured way to build these foundations, you can start here:

• AI Academy

• AI Literacy Fundamentals

You don't need to treat it as a big training programme. Even doing a small chunk each week alongside real work is enough to raise the baseline quickly.

Literacy first, then everything else

Once you've got these basics down, the rest of your AI decisions get easier.

You'll know which tasks are safe to hand over for a draft, and you'll get better outputs with less fiddling.

If you want to go further, use your literacy as the starting point for one specific area of the business – marketing, operations, customer support, finance.

Pick one workflow, improve it, then move on to the next. That's how AI starts feeling truly useful.

If you're part of Enterprise Nation's Tech Hub programme, you'll also find more practical guides and support to help you build confidence with digital tools, including accounting and finance workflows.

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