Free AI Audit: What You Get, How It Works and How to Prepare

A free AI audit is a review of your processes, tools and goals that ends with a shortlist of AI use cases, ranked by the value they would bring and the effort they would take. Some providers call it an AI readiness assessment or an AI opportunity assessment. The idea is the same: find the few places where AI clearly pays off before you spend money on building anything.

One clarification, because the term is used in two ways. An "AI audit" can also mean auditing an existing AI system for bias, security or regulatory compliance, for example against the EU AI Act. That is a different service. This article is about the first meaning: finding where AI should be used in your business.

A good report is short, specific and honest. It should include:

• A summary in plain language. Two or three sentences a manager can read in a minute.
• The tasks that cost the most time today. Based on your answers, with rough volumes where you gave them.
• Use cases ranked by value and effort. Not a list of everything AI can do, but the few things worth doing in your company, in order.
• What each use case needs. Which systems it must connect to, which data it would use, and who on your side would be involved.
• Risks and data protection notes. Where personal data is involved, where human review is needed, and any hosting requirements you mentioned.
• A recommended first step. Usually one pilot, with a clear success measure.
• What not to do yet. Ideas that sound good but would not pay off, and why.

The last point matters most. If a report recommends everything, it was written to sell, not to help you decide.

Our audit is built around a short questionnaire, so you do not need to book a call or prepare a presentation.

1. Answer a few questions

You can answer in a chat with our audit assistant, which takes about three minutes, or in a classic five-step form, which takes about five. The questions cover:

• Your company: name, industry and team size.
• Where your team loses time: the areas you want to improve and the one task that takes the most time, in your own words.
• Your tools and data: the systems you use, where the information AI would need lives, and any data requirements such as keeping data in the EU.
• Your goals: what matters most, when you would like to start and, if you want to share it, a budget range.
• Where to send the report: your name and work email.

2. A specialist analyses your answers

An engineer reviews your processes, tools and goals and works out which use cases fit.

3. Your report arrives by email

You receive the AI use cases ranked by value and effort, with next steps. There is no obligation to do anything with it.

You can start your free AI audit here.

The quality of any audit depends on the quality of the answers. Ten minutes of thought before you start makes the report far more specific.

Pick one or two concrete tasks

"We want to use AI in sales" is hard to assess. "We answer about 200 emails a day about order status, by hand" is easy. Describe what happens, who does it and how often.

Estimate the time it takes

A rough weekly figure is enough: under 10 hours, 10 to 40, or more. This is what turns an idea into a business case.

List your tools

Name the CRM, ERP, help desk, email and messaging tools you use. AI that works inside these tools is far more useful than one more separate app.

Know where the information lives

If an assistant should answer customer questions, where are the answers today? A help centre, shared drives, a wiki, people's heads? Knowledge that is not written down is the most common blocker, and it is better to know early.

Note your data rules

If customer data must stay in the EU or on your own servers, say so. It affects which models and hosting options are possible.

Decide what success looks like

Faster replies, fewer hours on data entry, more qualified leads. One clear goal helps rank the options.

To show how much the answers matter, here is a made-up but typical example of a wholesale company with 40 employees.

A vague answer

"We would like to use AI in customer service." This leaves too many questions open. Which requests? How many? Where are the answers? The only honest recommendation is "tell us more".

A useful answer

"Our two-person sales office receives about 150 emails a day. Roughly half are questions about order status and delivery dates, which we answer by looking up the order in our ERP. The rest are new orders and complaints. It takes most of one person's day. We use Outlook and an ERP with an API. Customer data should stay in the EU."

What the audit can do with it

From that answer, a report can rank concrete options:

1. Order-status replies. High value, moderate effort. An AI step reads the email, finds the order in the ERP and drafts a reply for a person to approve. Approval can be dropped later for simple cases if quality is proven.
2. New order intake. Medium value, higher effort. Extracting order lines from emails into the ERP needs careful validation against product codes.
3. Complaints. Not recommended yet. The volume is low and each case needs judgement, so a person should keep handling them, perhaps with a summary prepared by AI.

The same company, with the same problem, gets a far more useful report simply by describing the work concretely.

You have four realistic options once the report arrives:

• Do nothing for now. If the audit shows AI is not worth it yet, that is a useful result too.
• Use tools you already have. Some use cases are covered by features in software you already pay for. A good report will say so.
• Build it yourself. If you have developers, the report gives them a ranked starting point.
• Run a pilot with us. We build one use case on your real data, with success criteria agreed up front, and you decide on a go or no-go afterwards. Pilot and integration are quoted after the audit, based on your scope.

If you want to understand the later stages first, read AI automation services: what they include and how to choose a provider.

It is a fair question. The honest answer: the audit is how we find projects that are worth doing, for you and for us. Some companies who receive a report go on to run a pilot. Many do not, and that is fine.

There are a few things the audit is not. It is not a full process consulting engagement, it does not include building anything, and it is based on what you tell us rather than on access to your systems. Its job is to give you a clear, ranked starting point at no cost and without a sales call.

Free AI audits are offered by consultancies, agencies, freelancers and software vendors. Some are genuinely useful. Others are a sales call with a different name. Look for these signs:

• It asks about your processes first. Questions about tasks, volumes and tools come before questions about budget.
• You get a written result. A report you can share internally, not only a conversation.
• The shortlist is ranked and specific. Use cases tied to your tasks, not a generic list of AI features.
• It includes honest "no" answers. Some ideas should not be built yet, and a credible audit says which.
• Data handling is clear. You know what happens to your answers and who sees them.
• It is tool-neutral. If every recommendation leads to the vendor's own product, the audit is a product demo.

If you also need help deciding whether to bring in outside help at all, see AI consultant for small business: when you need one and what to expect.

A free AI audit is the cheapest way to replace a vague idea with a ranked, specific plan. It works best when you bring one or two concrete tasks, a rough idea of the time they take, and a clear view of your tools and data rules. The result should tell you what to do first, and just as clearly, what not to do yet.

When you are ready, start your free AI audit. It takes a few minutes, and the report arrives by email.